There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution...There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.展开更多
Salience theory has been proposed as a new stock trading strategy.To assess the validity of this proposal,a complex decision trading system was constructed based on salience theory,a variational mode decomposition(VMD...Salience theory has been proposed as a new stock trading strategy.To assess the validity of this proposal,a complex decision trading system was constructed based on salience theory,a variational mode decomposition(VMD)model,a bidirectional gated recurrent unit(BiGRU)model,and high-frequency trading.The system selected 30 Chinese new energy concept stocks,ranked the stocks using salience theory,and selected the top and bottom three stocks for two portfolios.Twelve stages were established,following which the VMD and BiGRU models were applied to the predictions.The final predicted annualized returns for the high ST(salience theory value)group A(GA)and low ST group B(GB)were 194.06%and 165.88%,respectively.This finding validates the powerful utility of salience theory and deep learning to analyze the Chinese new energy market.Moreover,it explains the theoretical practicality issues that the short selling restriction is the essential reason,or even perhaps the only reason,that leads to the strength of salience theory.展开更多
The oil-based mud(OBM) borehole measurement environment presents significant limitations on the application of existing electrical logging instruments in high-resistance formations. In this paper, we propose a novel l...The oil-based mud(OBM) borehole measurement environment presents significant limitations on the application of existing electrical logging instruments in high-resistance formations. In this paper, we propose a novel logging method for detection of high-resistance formations in OBM using highfrequency electrodes. The method addresses the issue of shallow depth of investigation(DOI) in existing electrical logging instruments, while simultaneously ensuring the vertical resolution. Based on the principle of current continuity, the total impedance of the loop is obtained by equating the measurement loop to the series form of a capacitively coupled circuit. and its validity is verified in a homogeneous formation model and a radial two-layer formation model with a mud standoff. Then, the instrument operating frequency and electrode system parameters were preferentially determined by numerical simulation, and the effect of mud gap on impedance measurement was investigated. Subsequently, the DOI of the instrument was investigated utilizing the pseudo-geometric factor defined by the real part of impedance. It was determined that the detection depth of the instrument is 8.74 cm, while the effective vertical resolution was not less than 2 cm. Finally, a focused high-frequency electrode-type instrument was designed by introducing a pair of focused electrodes, which effectively enhanced the DOI of the instrument and was successfully deployed in the Oklahoma formation model. The simulation results demonstrate that the novel method can achieve a detection depth of 17.40 cm in highly-resistive formations drilling with OBM, which is approximately twice the depth of detection of the existing oil-based mud microimager instruments. Furthermore, its effective vertical resolution remains at or above 2 cm,which is comparable to the resolution of the existing OBM electrical logging instrument.展开更多
Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between Octob...Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between October 2022 and October 2024 were selected for high-frequency ultrasound diagnosis.The diagnostic efficacy of high-frequency ultrasound was evaluated by comparing it with the results of surgical pathology.Results:High-frequency ultrasound detected 50 benign nodules,primarily breast fibroadenomas,and 35 malignant nodules,mainly breast ductal carcinoma in situ.Based on surgical pathology results,the diagnostic accuracy of high-frequency ultrasound was 96.47%,specificity was 97.96%,and sensitivity was 94.44%.In high-frequency ultrasound diagnosis,the proportion of grade III and IV blood flow in malignant nodules was higher than that in benign nodules,while the proportion of regular shape and clear margins was lower.The proportion of microcalcifications and posterior echo attenuation was higher in malignant nodules,and the resistance index(RI)and peak blood flow velocity were lower than those in benign nodules(P<0.05).Conclusion:High-frequency ultrasound can effectively differentiate benign and malignant breast micronodules,determine specific nodule types,and exhibits high diagnostic accuracy and sensitivity.Additionally,benign and malignant nodules can be differentiated based on the grading of blood flow signals,sonographic features,and blood flow velocity,providing reasonable guidance for subsequent treatment plans.展开更多
China has a long history of coal mining,among which open-pit coal mines have a large number of small coal mine goafs underground.The distribution,shape,structure and other characteristics of goafs are isolated and dis...China has a long history of coal mining,among which open-pit coal mines have a large number of small coal mine goafs underground.The distribution,shape,structure and other characteristics of goafs are isolated and discontinuous,and there is no definite geological law to follow,which seriously threatens the safety of coal mine production and personnel life.Conventional ground geophysical methods have low accuracy in detecting goaf areas affected by mechanical interference from open-pit mines,especially for waterless goaf areas,which cannot be detected by existing methods.This article proposes the use of high-frequency electromagnetic waves for goaf detection.The feasibility of using drilling radar to detect goaf was theoretically analyzed,and a goaf detection model was established.The response characteristics of different fillers in the goaf under different frequencies of high-frequency electromagnetic waves were simulated and analyzed.In a certain open-pit mine in Inner Mongolia,100MHz high-frequency electromagnetic waves were used to detect the goaf through directional drilling on the ground.After detection,excavation verification was carried out,and the location of one goaf detected was verified.The results of engineering practice show that the application of high-frequency electromagnetic waves in goaf detection expands the detection radius of boreholes,has the advantages of high efficiency and accuracy,and has important theoretical and practical significance.展开更多
New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed s...New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed switching of power converters.To address this situation,this paper offers an in-depth review of HF interference problems and challenges originating from power electronic devices.First,the root cause of HF electromagnetic interference,i.e.,the resonant response of the parasitic parameters of the system to high-speed switching transients,is analyzed,and various scenarios of HF interference in power systems are highlighted.Next,the types of HF interference are summarized,with a focus on common-mode interference in grounding systems.This paper thoroughly reviews and compares various suppression methods for conducted HF interference.Finally,the challenges involved and suggestions for addressing emerging HF interference problems from the perspective of both power electronics equipment and power systems are discussed.This review aims to offer a structured understanding of HF interference problems and their suppression techniques for researchers and practitioners.展开更多
Single-shot ultrafast compressed imaging(UCI)is an effective tool for studying ultrafast dynamics in physics,chemistry,or material science because of its excellent high frame rate and large frame number.However,the ra...Single-shot ultrafast compressed imaging(UCI)is an effective tool for studying ultrafast dynamics in physics,chemistry,or material science because of its excellent high frame rate and large frame number.However,the random code(Rcode)used in traditional UCI will lead to low-frequency noise covering high-frequency information due to its uneven sampling interval,which is a great challenge in the fidelity of large-frame reconstruction.Here,a high-frequency enhanced compressed active photography(H-CAP)is proposed.By uniformizing the sampling interval of R-code,H-CAP capture the ultrafast process with a random uniform sampling mode.This sampling mode makes the high-frequency sampling energy dominant,which greatly suppresses the low-frequency noise blurring caused by R-code and achieves high-frequency information of image enhanced.The superior dynamic performance and large-frame reconstruction ability of H-CAP are verified by imaging optical self-focusing effect and static object,respectively.We applied H-CAP to the spatial-temporal characterization of double-pulse induced silicon surface ablation dynamics,which is performed within 220 frames in a single-shot of 300 ps.H-CAP provides a high-fidelity imaging method for observing ultrafast unrepeatable dynamic processes with large frames.展开更多
Objective:To analyze the therapeutic effect of high-frequency electrosurgical knife surgery guided by painless digestive endoscopy(PDE)in elderly patients with gastrointestinal polyps(GP).Methods:A total of 100 elderl...Objective:To analyze the therapeutic effect of high-frequency electrosurgical knife surgery guided by painless digestive endoscopy(PDE)in elderly patients with gastrointestinal polyps(GP).Methods:A total of 100 elderly GP patients admitted between June 2021 and December 2022 were selected.Patients were randomly divided into two groups:the painless group(50 cases)underwent high-frequency electrosurgical knife surgery guided by PDE,while the conventional group(50 cases)underwent the same surgery guided by traditional digestive endoscopy(DE).The total treatment efficacy,perioperative indicators,gastrointestinal hormone levels,oxidative stress(OS)markers,and complication rates were compared between the two groups.Results:The total treatment efficacy in the painless group was higher than that in the conventional group,and perioperative indicators were superior in the painless group(P<0.05).One week after treatment,the gastrointestinal hormone levels and OS-related markers in the painless group were better than those in the conventional group(P<0.05).The complication rate in the painless group was lower than in the conventional group(P<0.05).Conclusion:High-frequency electrosurgical knife surgery guided by PDE improves the effectiveness of polyp removal in elderly GP patients and accelerates postoperative recovery.It also protects gastrointestinal function,reduces postoperative OS,and ensures higher surgical safety.展开更多
Soft magnetic composites made from metallic magnetic particles with an easy magnetization plane(referred to as easy-plane metallic soft magnetic composites(SMC))are considered ideal materials for the next generation o...Soft magnetic composites made from metallic magnetic particles with an easy magnetization plane(referred to as easy-plane metallic soft magnetic composites(SMC))are considered ideal materials for the next generation of power electronic devices.This advantage is attributed to their ability to maintain high permeability at elevated frequencies.Despite these advantages,a definitive mathematical model that connects the high-frequency magnetic properties(e.g.,effective permeability)of easy-plane metallic SMCs to the intrinsic properties of the particles is still lacking.In this work,a theoretical calculation model for the effective permeability of easy-plane metallic SMCs was formulated.This model was derived from a skin effect-corrected Landau-Lifshitz-Gilbert(LLG)equation and integrated with effective medium theory incorporating inter-particle interaction.To validate the model,we prepared samples of easy-plane Y_(2)Co_(17)particle/PU SMCs with varying particle sizes and volume fractions.The experimental results showed a strong agreement with the calculated values.This research offers critical theoretical backing for the design and optimization of soft magnetic materials intended for high-frequency applications.展开更多
High-frequency pulsed(HFP)gas tungsten arc welding(GTAW)has shown excellent performance in welding of aluminum alloys in recent years,which makes itself a promisingly potential technique for part manufacturing in avia...High-frequency pulsed(HFP)gas tungsten arc welding(GTAW)has shown excellent performance in welding of aluminum alloys in recent years,which makes itself a promisingly potential technique for part manufacturing in aviation industry.However,existing researches generally focuses on the effect of a single parameter while lacks multivariable researches.Considering of the fact that gap and misalignment are inevitable in real part clamping,adaptive intelligent welding is usually used during automatic manufacturing,which means under the control of filler wire amount per length of a weld,other parameters including current,welding speed and wire feed speed during one single weld are changing according to the specific clamping situation.Therefore,the influence of specific energy input led by different welding parameters within one adaptive welding program on microstructure and mechanical property of the weld needs to be clarified.This study investigates the effect of welding heat input(ranging from 1048.3 J/mm to 825.6 J/mm within one adaptive welding program control)on the formation quality of 3.25 mm thick 6061 aluminum alloy joints fabricated by HFP-GTAW with 4043 filler wire.According to the obtained results,non-monotonic relationship between heat input and porosity,with an optimal minimum of 4.92%achieved at an intermediate heat input of 856.8 J/mm.The 21.2%decrease of energy input during welding process would reduce the average grain size in the weld center and adjacent to fusion line by 18.6%and 19.4%,respectively.The ratios between fluctuation range to minimum value in average yield and the relative ranges of yield strength and ultimate tensile strength across the tested heat inputs were 14.7%and 12.7%,respectively.The findings provide a general overview on how the microstructure and mechanical properties would fluctuate in an adaptively controlled HFP-GTAW fabricated aluminum alloy weld.展开更多
With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limite...With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.展开更多
High-frequency image technique has been widely applied in medical diagnosis recently. For high voltage protection, high speed stage and trigger control circuitry are difficult to implement a high-frequency ultrasound ...High-frequency image technique has been widely applied in medical diagnosis recently. For high voltage protection, high speed stage and trigger control circuitry are difficult to implement a high-frequency ultrasound imaging system. In this study, we utilized a linear servo with high noise tolerance and a novel multi-depth expression method to overcome those issues in developed high-speed image system. B-mode image of the chicken phantom by 25 MHz transducer shows the resolution of lateral and axial resolutions are up to 123 μm and 59 μm respectively. In addition, the experiment demonstrates that the axial resolution and depth of field (DOF) can be improved by time gain compensation(TGC) and multi-depth method. The results indicate that the proposed system could achieve over 24 fps for 1 mm scan distance and 100 lines per frame. In the future, the developed system is potential for other clinical applications such as ophthalmology and dermatology.展开更多
The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model ...The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model for epoxy resin encapsulated nano HFTs, which aims to precisely predict the temperature distribution inside the transformer in combination with the finite element method(FEM). A magnetothermal bidirectional coupling 3DTN model is established by analyzing the thermal conduction between the core, windings, and epoxy resin, while also considering the convection and radiation heat transfer mechanisms on the surface of the epoxy resin. The model considers the impact of loss distribution in the core and windings on the temperature field and adopts a simplified 1/2 thermal network model to reduce computational complexity. Furthermore, the results of FEM are compared with experimental results to verify the accuracy of the 3DTN model in predicting the temperature rise of nano HFT. The results show that the 3DTN model reduces errors by an average of 5.25% over the traditional two-dimensional thermal network(2DTN) model, particularly for temperature distributions in the windings and core. This paper provides a temperature rise prediction method for the thermal design and offers a theoretical basis and engineering guidance for the optimization of their thermal management systems.展开更多
Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybr...Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.展开更多
In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statist...In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.展开更多
This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastr...This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastrointestinal polyp resection were selected and randomly divided into a control group and an experimental group.The control group received routine nursing,while the experimental group implemented combined health education and dietary guidance on this basis.By comparing the recovery indicators of the two groups,it was found that the recovery speed of the experimental group was significantly faster than that of the control group,indicating that this combined intervention method can effectively promote patient recovery.展开更多
During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the i...During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.展开更多
Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware los...Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware loss function is proposed for accurate multistep wind speed forecasting.In this model,the wind speed data is first denoised using the maximal overlap discrete wavelet transform.Next,an encoder-decoder network based on a temporal convolutional network,bidirectional gated recurrent unit,and multihead self-attention is employed for forecasting.Additionally,to enhance the ability of the model to identify temporal dynamics,a shape-aware loss function,ITILDE-Q,is employed in the model.To verify the effectiveness of the proposed model,a comparative experiment and an ablation experiment were conducted using three datasets of measured wind speeds.Three error metrics and a similarity metric were adopted for comprehensive evaluation.The experimental results showed that the proposed model consistently outperforms benchmark models in all tested forecasting scenarios,with particularly pronounced differences in performance over longer forecast horizons.Furthermore,the synergistic interaction of the three key components contributes to the extraordinary performance of the proposed model.展开更多
Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning...Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.展开更多
Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the...Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).展开更多
基金supported by the National Nature Science Foundation of China(Nos.12027901 and 12041202)Synchrotron Radiation Joint Fund of University of Science and Technology of China(Nos.KY2090000059 and KY2090000054)。
文摘There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.
基金supported by the National Natural Science Foundation of China(Grant Nos.72032006 and 92146005).
文摘Salience theory has been proposed as a new stock trading strategy.To assess the validity of this proposal,a complex decision trading system was constructed based on salience theory,a variational mode decomposition(VMD)model,a bidirectional gated recurrent unit(BiGRU)model,and high-frequency trading.The system selected 30 Chinese new energy concept stocks,ranked the stocks using salience theory,and selected the top and bottom three stocks for two portfolios.Twelve stages were established,following which the VMD and BiGRU models were applied to the predictions.The final predicted annualized returns for the high ST(salience theory value)group A(GA)and low ST group B(GB)were 194.06%and 165.88%,respectively.This finding validates the powerful utility of salience theory and deep learning to analyze the Chinese new energy market.Moreover,it explains the theoretical practicality issues that the short selling restriction is the essential reason,or even perhaps the only reason,that leads to the strength of salience theory.
基金the National Natural Science Foundation of China(42074134,42474152,42374150)CNPC Innovation Found(2024DQ02-0152).
文摘The oil-based mud(OBM) borehole measurement environment presents significant limitations on the application of existing electrical logging instruments in high-resistance formations. In this paper, we propose a novel logging method for detection of high-resistance formations in OBM using highfrequency electrodes. The method addresses the issue of shallow depth of investigation(DOI) in existing electrical logging instruments, while simultaneously ensuring the vertical resolution. Based on the principle of current continuity, the total impedance of the loop is obtained by equating the measurement loop to the series form of a capacitively coupled circuit. and its validity is verified in a homogeneous formation model and a radial two-layer formation model with a mud standoff. Then, the instrument operating frequency and electrode system parameters were preferentially determined by numerical simulation, and the effect of mud gap on impedance measurement was investigated. Subsequently, the DOI of the instrument was investigated utilizing the pseudo-geometric factor defined by the real part of impedance. It was determined that the detection depth of the instrument is 8.74 cm, while the effective vertical resolution was not less than 2 cm. Finally, a focused high-frequency electrode-type instrument was designed by introducing a pair of focused electrodes, which effectively enhanced the DOI of the instrument and was successfully deployed in the Oklahoma formation model. The simulation results demonstrate that the novel method can achieve a detection depth of 17.40 cm in highly-resistive formations drilling with OBM, which is approximately twice the depth of detection of the existing oil-based mud microimager instruments. Furthermore, its effective vertical resolution remains at or above 2 cm,which is comparable to the resolution of the existing OBM electrical logging instrument.
文摘Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between October 2022 and October 2024 were selected for high-frequency ultrasound diagnosis.The diagnostic efficacy of high-frequency ultrasound was evaluated by comparing it with the results of surgical pathology.Results:High-frequency ultrasound detected 50 benign nodules,primarily breast fibroadenomas,and 35 malignant nodules,mainly breast ductal carcinoma in situ.Based on surgical pathology results,the diagnostic accuracy of high-frequency ultrasound was 96.47%,specificity was 97.96%,and sensitivity was 94.44%.In high-frequency ultrasound diagnosis,the proportion of grade III and IV blood flow in malignant nodules was higher than that in benign nodules,while the proportion of regular shape and clear margins was lower.The proportion of microcalcifications and posterior echo attenuation was higher in malignant nodules,and the resistance index(RI)and peak blood flow velocity were lower than those in benign nodules(P<0.05).Conclusion:High-frequency ultrasound can effectively differentiate benign and malignant breast micronodules,determine specific nodule types,and exhibits high diagnostic accuracy and sensitivity.Additionally,benign and malignant nodules can be differentiated based on the grading of blood flow signals,sonographic features,and blood flow velocity,providing reasonable guidance for subsequent treatment plans.
文摘China has a long history of coal mining,among which open-pit coal mines have a large number of small coal mine goafs underground.The distribution,shape,structure and other characteristics of goafs are isolated and discontinuous,and there is no definite geological law to follow,which seriously threatens the safety of coal mine production and personnel life.Conventional ground geophysical methods have low accuracy in detecting goaf areas affected by mechanical interference from open-pit mines,especially for waterless goaf areas,which cannot be detected by existing methods.This article proposes the use of high-frequency electromagnetic waves for goaf detection.The feasibility of using drilling radar to detect goaf was theoretically analyzed,and a goaf detection model was established.The response characteristics of different fillers in the goaf under different frequencies of high-frequency electromagnetic waves were simulated and analyzed.In a certain open-pit mine in Inner Mongolia,100MHz high-frequency electromagnetic waves were used to detect the goaf through directional drilling on the ground.After detection,excavation verification was carried out,and the location of one goaf detected was verified.The results of engineering practice show that the application of high-frequency electromagnetic waves in goaf detection expands the detection radius of boreholes,has the advantages of high efficiency and accuracy,and has important theoretical and practical significance.
基金supported by the science and technology project of State Grid Shanghai Municipal Electric Power Company(No.52094023003L).
文摘New electric power systems characterized by a high proportion of renewable energy and power electronics equipment face significant challenges due to high-frequency(HF)electromagnetic interference from the high-speed switching of power converters.To address this situation,this paper offers an in-depth review of HF interference problems and challenges originating from power electronic devices.First,the root cause of HF electromagnetic interference,i.e.,the resonant response of the parasitic parameters of the system to high-speed switching transients,is analyzed,and various scenarios of HF interference in power systems are highlighted.Next,the types of HF interference are summarized,with a focus on common-mode interference in grounding systems.This paper thoroughly reviews and compares various suppression methods for conducted HF interference.Finally,the challenges involved and suggestions for addressing emerging HF interference problems from the perspective of both power electronics equipment and power systems are discussed.This review aims to offer a structured understanding of HF interference problems and their suppression techniques for researchers and practitioners.
基金supported by the National Science Foundation of China(No.12127806,No.62175195 and No.12304382)the International Joint Research Laboratory for Micro/Nano Manufacturing and Measurement Technologies.
文摘Single-shot ultrafast compressed imaging(UCI)is an effective tool for studying ultrafast dynamics in physics,chemistry,or material science because of its excellent high frame rate and large frame number.However,the random code(Rcode)used in traditional UCI will lead to low-frequency noise covering high-frequency information due to its uneven sampling interval,which is a great challenge in the fidelity of large-frame reconstruction.Here,a high-frequency enhanced compressed active photography(H-CAP)is proposed.By uniformizing the sampling interval of R-code,H-CAP capture the ultrafast process with a random uniform sampling mode.This sampling mode makes the high-frequency sampling energy dominant,which greatly suppresses the low-frequency noise blurring caused by R-code and achieves high-frequency information of image enhanced.The superior dynamic performance and large-frame reconstruction ability of H-CAP are verified by imaging optical self-focusing effect and static object,respectively.We applied H-CAP to the spatial-temporal characterization of double-pulse induced silicon surface ablation dynamics,which is performed within 220 frames in a single-shot of 300 ps.H-CAP provides a high-fidelity imaging method for observing ultrafast unrepeatable dynamic processes with large frames.
文摘Objective:To analyze the therapeutic effect of high-frequency electrosurgical knife surgery guided by painless digestive endoscopy(PDE)in elderly patients with gastrointestinal polyps(GP).Methods:A total of 100 elderly GP patients admitted between June 2021 and December 2022 were selected.Patients were randomly divided into two groups:the painless group(50 cases)underwent high-frequency electrosurgical knife surgery guided by PDE,while the conventional group(50 cases)underwent the same surgery guided by traditional digestive endoscopy(DE).The total treatment efficacy,perioperative indicators,gastrointestinal hormone levels,oxidative stress(OS)markers,and complication rates were compared between the two groups.Results:The total treatment efficacy in the painless group was higher than that in the conventional group,and perioperative indicators were superior in the painless group(P<0.05).One week after treatment,the gastrointestinal hormone levels and OS-related markers in the painless group were better than those in the conventional group(P<0.05).The complication rate in the painless group was lower than in the conventional group(P<0.05).Conclusion:High-frequency electrosurgical knife surgery guided by PDE improves the effectiveness of polyp removal in elderly GP patients and accelerates postoperative recovery.It also protects gastrointestinal function,reduces postoperative OS,and ensures higher surgical safety.
基金supported by the National Key R&D Program of China(Grant No.2021YFB3501300)the 9th Research Institute of China Electronics Technology Group Corporation’s open projects(Grant No.2024SK-002-01)the Science and Technology Project of Gansu Province(Grant No.22YF7GA001).
文摘Soft magnetic composites made from metallic magnetic particles with an easy magnetization plane(referred to as easy-plane metallic soft magnetic composites(SMC))are considered ideal materials for the next generation of power electronic devices.This advantage is attributed to their ability to maintain high permeability at elevated frequencies.Despite these advantages,a definitive mathematical model that connects the high-frequency magnetic properties(e.g.,effective permeability)of easy-plane metallic SMCs to the intrinsic properties of the particles is still lacking.In this work,a theoretical calculation model for the effective permeability of easy-plane metallic SMCs was formulated.This model was derived from a skin effect-corrected Landau-Lifshitz-Gilbert(LLG)equation and integrated with effective medium theory incorporating inter-particle interaction.To validate the model,we prepared samples of easy-plane Y_(2)Co_(17)particle/PU SMCs with varying particle sizes and volume fractions.The experimental results showed a strong agreement with the calculated values.This research offers critical theoretical backing for the design and optimization of soft magnetic materials intended for high-frequency applications.
基金supported by the Commercial Aircraft Corporation of China Ltd.(Grant No.COMAC-SFGS-2024–569)Fundamental Research Funds for the Central Universities and Institute of Marine Equipment,Shanghai Rising-Star Program of Science and Technology Commission of Shanghai Municipality(Grant No.23QA1404700)+1 种基金National Natural Science Foundation of China(Grant No.52475384,52505409)China Postdoctoral Science Foundation(Grant No.2024M761963)。
文摘High-frequency pulsed(HFP)gas tungsten arc welding(GTAW)has shown excellent performance in welding of aluminum alloys in recent years,which makes itself a promisingly potential technique for part manufacturing in aviation industry.However,existing researches generally focuses on the effect of a single parameter while lacks multivariable researches.Considering of the fact that gap and misalignment are inevitable in real part clamping,adaptive intelligent welding is usually used during automatic manufacturing,which means under the control of filler wire amount per length of a weld,other parameters including current,welding speed and wire feed speed during one single weld are changing according to the specific clamping situation.Therefore,the influence of specific energy input led by different welding parameters within one adaptive welding program on microstructure and mechanical property of the weld needs to be clarified.This study investigates the effect of welding heat input(ranging from 1048.3 J/mm to 825.6 J/mm within one adaptive welding program control)on the formation quality of 3.25 mm thick 6061 aluminum alloy joints fabricated by HFP-GTAW with 4043 filler wire.According to the obtained results,non-monotonic relationship between heat input and porosity,with an optimal minimum of 4.92%achieved at an intermediate heat input of 856.8 J/mm.The 21.2%decrease of energy input during welding process would reduce the average grain size in the weld center and adjacent to fusion line by 18.6%and 19.4%,respectively.The ratios between fluctuation range to minimum value in average yield and the relative ranges of yield strength and ultimate tensile strength across the tested heat inputs were 14.7%and 12.7%,respectively.The findings provide a general overview on how the microstructure and mechanical properties would fluctuate in an adaptively controlled HFP-GTAW fabricated aluminum alloy weld.
基金National Natural Science Foundation of China, grant number 52177074.
文摘With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.
文摘High-frequency image technique has been widely applied in medical diagnosis recently. For high voltage protection, high speed stage and trigger control circuitry are difficult to implement a high-frequency ultrasound imaging system. In this study, we utilized a linear servo with high noise tolerance and a novel multi-depth expression method to overcome those issues in developed high-speed image system. B-mode image of the chicken phantom by 25 MHz transducer shows the resolution of lateral and axial resolutions are up to 123 μm and 59 μm respectively. In addition, the experiment demonstrates that the axial resolution and depth of field (DOF) can be improved by time gain compensation(TGC) and multi-depth method. The results indicate that the proposed system could achieve over 24 fps for 1 mm scan distance and 100 lines per frame. In the future, the developed system is potential for other clinical applications such as ophthalmology and dermatology.
基金supported by the Project of the National Key Research and Development Program of China under Grant 2022YFB2404100。
文摘The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model for epoxy resin encapsulated nano HFTs, which aims to precisely predict the temperature distribution inside the transformer in combination with the finite element method(FEM). A magnetothermal bidirectional coupling 3DTN model is established by analyzing the thermal conduction between the core, windings, and epoxy resin, while also considering the convection and radiation heat transfer mechanisms on the surface of the epoxy resin. The model considers the impact of loss distribution in the core and windings on the temperature field and adopts a simplified 1/2 thermal network model to reduce computational complexity. Furthermore, the results of FEM are compared with experimental results to verify the accuracy of the 3DTN model in predicting the temperature rise of nano HFT. The results show that the 3DTN model reduces errors by an average of 5.25% over the traditional two-dimensional thermal network(2DTN) model, particularly for temperature distributions in the windings and core. This paper provides a temperature rise prediction method for the thermal design and offers a theoretical basis and engineering guidance for the optimization of their thermal management systems.
文摘Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.
基金supported by the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202307)the Basic Research Fund of CAMS(No.2023Z016)+1 种基金the National Natural Scientific Foundation of China(No.42275037)the Jiangsu Collaborative Innovation Center for Climate Change。
文摘In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.
文摘This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastrointestinal polyp resection were selected and randomly divided into a control group and an experimental group.The control group received routine nursing,while the experimental group implemented combined health education and dietary guidance on this basis.By comparing the recovery indicators of the two groups,it was found that the recovery speed of the experimental group was significantly faster than that of the control group,indicating that this combined intervention method can effectively promote patient recovery.
基金support from the National Natural Science Foundation of China(No.52271287)funding from the State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation,Tianjin University。
文摘During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.
基金supported by the National Natural Science Foundation of China(No.52171284)。
文摘Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware loss function is proposed for accurate multistep wind speed forecasting.In this model,the wind speed data is first denoised using the maximal overlap discrete wavelet transform.Next,an encoder-decoder network based on a temporal convolutional network,bidirectional gated recurrent unit,and multihead self-attention is employed for forecasting.Additionally,to enhance the ability of the model to identify temporal dynamics,a shape-aware loss function,ITILDE-Q,is employed in the model.To verify the effectiveness of the proposed model,a comparative experiment and an ablation experiment were conducted using three datasets of measured wind speeds.Three error metrics and a similarity metric were adopted for comprehensive evaluation.The experimental results showed that the proposed model consistently outperforms benchmark models in all tested forecasting scenarios,with particularly pronounced differences in performance over longer forecast horizons.Furthermore,the synergistic interaction of the three key components contributes to the extraordinary performance of the proposed model.
基金funded by Science and Technology Research and Development Program Project of China Railway Group Limited(No.2023-Major-02)National Natural Science Foundation of China(Grant No.52378200)Sichuan Science and Technology Program(Grant No.2024NSFSC0017).
文摘Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.
文摘Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).
