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
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromat...[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.展开更多
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
The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and propertie...The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and properties of AM60 based alloys.AM60-0.2La alloy showed excellent mechanical properties.The ultimate tensile strength,yield strength,and elongation of(288.0±1.7)MPa,(158.0±1.0)MPa,and(22.0±3.0)%were achieved in AM60-0.2La alloy.Besides,AM60-0.2La alloy exhibited the best corrosion resistance(0.29 mm/a)and fluidity among the investigated four alloys.The excellent mechanical properties and corrosion resistance are mainly attributed to the grain refinement strengthening,low porosity,and low content of large shrinkage porosity,promising for super-sized integrated automotive components.展开更多
Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characte...Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characteristics of C.gigas from different sources(ploidy,region,size,and culture mode),C.gigas from various ploidy(diploid and triploid),regions(Rushan,Off-site fattening,and Rongcheng),sizes(small,medium,and large)and culture modes(nearshore and offshore)were selected for comparative analyses.The nutritional components(moisture,protein,fat,and mineral),flavor substances(taste amino acids,nucleotides,and succinic acid),and functional indices(eicosapentaenoic acid(EPA),docosahexaenoic acid(DHA),and taurine)of C.gigas were determined.Principal component analysis(PCA)was used to comprehensively evaluate the oysters and investigate the variations in nutritional quality.The PCA results indicate that protein,essential fatty acids,selenium,zinc,taste amino acids,taurine,EPA,and DHA were core components contributing to 82.25%of the cumulative variance,providing a more comprehensive reflection of the nutrient composition of C.gigas.The extensive quality rankings for the C.gigas were as follows:diploid>triploid,Rushan>fattening>Rongcheng,medium>large>small,and offshore>nearshore.The score rank revealed that diploid oysters of medium-size from Rushan demonstrated superior nutritional quality compared to other tested samples.This is the first comprehensive and systematic investigation of C.gigas in northern China to reveal the feature of nutrients,flavor,and functional components.The study provided data support for the culture,consumption,processing,research,and nutritional quality improvement of oyster industry.展开更多
The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and redu...The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and reduce forming loads.However,the absence of compatible forming equipment makes it difficult to control the constraint in the unloaded zones during the forming process.This difficulty complicates coordination and control of deformation,particularly for asymmetric rib-web components.Additionally,the current implementation involves multi-fire heating,a long process flow,and high energy consumption,which limits the popularization and application of the local loading process.In this study,a new multi-pass local loading hydraulic forming apparatus that can quickly and reliably switch between heavy-load deformation and low-load constraint for different local loading sub-dies was developed.A 10-tonne laboratory prototype was developed,and the forming characteristics during the forming process as well as the response characteristics of the hydraulic system during the multi-pass intermittent local loading of rib-web component were investigated using numerical simulations and physical experiments.Results indicated that,compared to a whole loading process with the same initial geometry of billet,the total forming load(i.e.,the sum of loaded and restrained loads)is reduced by more than 40%with the local loading process,and by nearly 50%with multi-pass local loading.The multi-pass local loading process allows for more effective control of material flow compared to single-pass local loading,leading to improved cavity filling and reduced flow line disturbance.For a large-scale,complex titanium alloy bulkhead,the cavity filling problem was addressed by optimizing the multi-pass local loading path with an unequal thickness billet.The dynamic performance of the multi-pass local loading hydraulic system was found to be robust,with stable pressure transitions during motion and load switching for the sub-die(s).The dynamic characteristic of the hydraulic cylinder when switching from non-moving/unloaded state to a moving/loading state are consistent whether a load is present or not.However,the dynamic characteristics differ when switching from a moving/loading state to non-moving/unloaded state,showing opposite behavior.The developed hydraulic drive mechanism provides a way for implementation of multi-pass local loading without auxiliary operation and extra heating.The results of the study provide a foundation for the industrial production of large-scale,complex components with reduced force requirement and low-energy consumption.展开更多
Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing ...Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing significant challenges to model robustness and deployment.Using multivariate time-series data from Scania trucks,this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification.First,the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness,allowing LightGBM to leverage its inherent split rules without ad-hoc imputation.Then,a two-stage LightGBM framework is developed for fault detection and severity classification:Stage A performs safety-prioritized fault screening(normal vs.fault)with a false-negativeweighted objective,and Stage B refines the detected faults into four severity levels through a cascaded hierarchy of binary classifiers.Under the official cost matrix of the IDA Industrial Challenge,the framework achieves total misclassification costs of 36,113(validation)and 36,314(test),outperforming XGBoost and Bi-LSTM by 3.8%-13.5%while maintaining high recall for the safety-critical class(0.83 validation,0.77 test).These results demonstrate that the proposed approach not only improves predictive accuracy but also provides a practical and deployable PdM solution that reduces maintenance cost,enhances fleet safety,and supports data-driven decision-making in industrial environments.展开更多
Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.Thi...Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.This review systematically explores the therapeutic components of acupuncture,emphasizing the interplay between sensory nerve characteristics and neural signaling pathways.Key factors such as acupoint location,needling depth,stimulation intensity,retention time,and the induction of sensations(e.g.,Deqi)are analyzed for their roles in neural activation and clinical outcomes.The review highlights how variations in spinal segment targeting,tissue-specific receptor activation,and stimulation modalities(e.g.,manual acupuncture,electroacupuncture,moxibustion)influence therapeutic effects.Emerging evidence underscores the significance of ion channels,dermatomes,myotomes,and genespecific pathways in mediating systemic effects.Additionally,the differential roles of mechanical,thermal and nociceptive stimuli and the temporal dynamics of sensory and immune responses are addressed.While insights from animal models have advanced our understanding,their translation to clinical practice requires further investigation.This comprehensive review identifies critical parameters for optimizing acupuncture therapy,advocating for individualized treatment strategies informed by neuroanatomical and neurophysiological principles,ultimately enhancing its precision and efficacy in modern medicine.展开更多
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants h...Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.展开更多
Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high com...Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high computational complexity and insufficient capture of high-frequency phase aberration components,so we proposed a Principal-Component-Analysis-based method for representing phase aberrations.This paper discusses the factors influencing the accuracy of restoration,mainly including the sample space size and the sampling interval of D/r_(0),on the basis of characterizing phase aberrations by Principal Components(PCs).The experimental results show that a larger D/r_(0)sampling interval can ensure the generalization ability and robustness of the principal components in the case of a limited amount of original data,which can help to achieve high-precision deployment of the model in practical applications quickly.In the environment with relatively strong turbulence in the test set of D/r_(0)=24,the use of 34 terms of PCs can improve the corrected Strehl ratio(SR)from 0.007 to 0.1585,while the Strehl ratio of the light spot after restoration using 34 terms of ZPs is only 0.0215,demonstrating almost no correction effect.The results indicate that PCs can serve as a better alternative in representing and restoring the characteristics of atmospheric turbulence induced phase aberrations.These findings pave the way to use PCs of phase aberrations with fewer terms than traditional ZPs to achieve data dimensionality reduction,and offer a reference to accelerate and stabilize the model and deep learning based adaptive optics correction.展开更多
Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. Thi...Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.展开更多
Dear Editor,Local recurrence and cervical lymph node metastases are major causes of mortality in patients with head and neck squamous cell carcinoma(HNSCC).To date,none of the proposed strategies for predicting outcom...Dear Editor,Local recurrence and cervical lymph node metastases are major causes of mortality in patients with head and neck squamous cell carcinoma(HNSCC).To date,none of the proposed strategies for predicting outcomes in this disease have proven fully effective,and a comprehensive physical examination remains the primary method for early detection and monitoring of HNSCC.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
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.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金Supported by Jiangxi Education Department Project(GJJ201533)University-level Project of Gannan Medical University(YB201902).
文摘[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.
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financially supported by the National Key Research and Development Program of China(Nos.2022YFB3709300,2021YFB3701000)the National Natural Science Foundation of China(Nos.52271090,52071036,U2037601,U21A2048)+1 种基金Chongqing Science and Technology Commission,China(Nos.CSTB2022TIAD-KPX0021,CSTC2024YCJHBGZXM0164,CSTB2024TIAD-KPX0001)the Fundamental Research Funds for the Central Universities,China(No.2022CDJDX-002)。
文摘The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and properties of AM60 based alloys.AM60-0.2La alloy showed excellent mechanical properties.The ultimate tensile strength,yield strength,and elongation of(288.0±1.7)MPa,(158.0±1.0)MPa,and(22.0±3.0)%were achieved in AM60-0.2La alloy.Besides,AM60-0.2La alloy exhibited the best corrosion resistance(0.29 mm/a)and fluidity among the investigated four alloys.The excellent mechanical properties and corrosion resistance are mainly attributed to the grain refinement strengthening,low porosity,and low content of large shrinkage porosity,promising for super-sized integrated automotive components.
基金Supported by the Central Public-interest Scientific Institution Basal Research Fund,YSFRI,CAFS(No.20603022024016)the Central Public-interest Scientific Institution Basal Research Fund,CAFS(Nos.2023TD52,2023TD76)the earmarked fund for CARS(No.CARS-49)。
文摘Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characteristics of C.gigas from different sources(ploidy,region,size,and culture mode),C.gigas from various ploidy(diploid and triploid),regions(Rushan,Off-site fattening,and Rongcheng),sizes(small,medium,and large)and culture modes(nearshore and offshore)were selected for comparative analyses.The nutritional components(moisture,protein,fat,and mineral),flavor substances(taste amino acids,nucleotides,and succinic acid),and functional indices(eicosapentaenoic acid(EPA),docosahexaenoic acid(DHA),and taurine)of C.gigas were determined.Principal component analysis(PCA)was used to comprehensively evaluate the oysters and investigate the variations in nutritional quality.The PCA results indicate that protein,essential fatty acids,selenium,zinc,taste amino acids,taurine,EPA,and DHA were core components contributing to 82.25%of the cumulative variance,providing a more comprehensive reflection of the nutrient composition of C.gigas.The extensive quality rankings for the C.gigas were as follows:diploid>triploid,Rushan>fattening>Rongcheng,medium>large>small,and offshore>nearshore.The score rank revealed that diploid oysters of medium-size from Rushan demonstrated superior nutritional quality compared to other tested samples.This is the first comprehensive and systematic investigation of C.gigas in northern China to reveal the feature of nutrients,flavor,and functional components.The study provided data support for the culture,consumption,processing,research,and nutritional quality improvement of oyster industry.
基金the supports of the National Natural Science Foundation of China(Grant No.52375378)。
文摘The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and reduce forming loads.However,the absence of compatible forming equipment makes it difficult to control the constraint in the unloaded zones during the forming process.This difficulty complicates coordination and control of deformation,particularly for asymmetric rib-web components.Additionally,the current implementation involves multi-fire heating,a long process flow,and high energy consumption,which limits the popularization and application of the local loading process.In this study,a new multi-pass local loading hydraulic forming apparatus that can quickly and reliably switch between heavy-load deformation and low-load constraint for different local loading sub-dies was developed.A 10-tonne laboratory prototype was developed,and the forming characteristics during the forming process as well as the response characteristics of the hydraulic system during the multi-pass intermittent local loading of rib-web component were investigated using numerical simulations and physical experiments.Results indicated that,compared to a whole loading process with the same initial geometry of billet,the total forming load(i.e.,the sum of loaded and restrained loads)is reduced by more than 40%with the local loading process,and by nearly 50%with multi-pass local loading.The multi-pass local loading process allows for more effective control of material flow compared to single-pass local loading,leading to improved cavity filling and reduced flow line disturbance.For a large-scale,complex titanium alloy bulkhead,the cavity filling problem was addressed by optimizing the multi-pass local loading path with an unequal thickness billet.The dynamic performance of the multi-pass local loading hydraulic system was found to be robust,with stable pressure transitions during motion and load switching for the sub-die(s).The dynamic characteristic of the hydraulic cylinder when switching from non-moving/unloaded state to a moving/loading state are consistent whether a load is present or not.However,the dynamic characteristics differ when switching from a moving/loading state to non-moving/unloaded state,showing opposite behavior.The developed hydraulic drive mechanism provides a way for implementation of multi-pass local loading without auxiliary operation and extra heating.The results of the study provide a foundation for the industrial production of large-scale,complex components with reduced force requirement and low-energy consumption.
基金supported by the GRRC program of Gyeonggi province[GRRC KGU 2023-B01,Research on Intelligent Industrial Data Analytics].
文摘Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing significant challenges to model robustness and deployment.Using multivariate time-series data from Scania trucks,this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification.First,the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness,allowing LightGBM to leverage its inherent split rules without ad-hoc imputation.Then,a two-stage LightGBM framework is developed for fault detection and severity classification:Stage A performs safety-prioritized fault screening(normal vs.fault)with a false-negativeweighted objective,and Stage B refines the detected faults into four severity levels through a cascaded hierarchy of binary classifiers.Under the official cost matrix of the IDA Industrial Challenge,the framework achieves total misclassification costs of 36,113(validation)and 36,314(test),outperforming XGBoost and Bi-LSTM by 3.8%-13.5%while maintaining high recall for the safety-critical class(0.83 validation,0.77 test).These results demonstrate that the proposed approach not only improves predictive accuracy but also provides a practical and deployable PdM solution that reduces maintenance cost,enhances fleet safety,and supports data-driven decision-making in industrial environments.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2020R1C1C1004107)。
文摘Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.This review systematically explores the therapeutic components of acupuncture,emphasizing the interplay between sensory nerve characteristics and neural signaling pathways.Key factors such as acupoint location,needling depth,stimulation intensity,retention time,and the induction of sensations(e.g.,Deqi)are analyzed for their roles in neural activation and clinical outcomes.The review highlights how variations in spinal segment targeting,tissue-specific receptor activation,and stimulation modalities(e.g.,manual acupuncture,electroacupuncture,moxibustion)influence therapeutic effects.Emerging evidence underscores the significance of ion channels,dermatomes,myotomes,and genespecific pathways in mediating systemic effects.Additionally,the differential roles of mechanical,thermal and nociceptive stimuli and the temporal dynamics of sensory and immune responses are addressed.While insights from animal models have advanced our understanding,their translation to clinical practice requires further investigation.This comprehensive review identifies critical parameters for optimizing acupuncture therapy,advocating for individualized treatment strategies informed by neuroanatomical and neurophysiological principles,ultimately enhancing its precision and efficacy in modern medicine.
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
基金supported by the key project at the central government level:The ability establishment of sustainable use for valuable Chinese medicine resources(Grant number 2060302)the National Natural Science Foundation of China(Grant number 82373982,82173929).
文摘Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.
文摘Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high computational complexity and insufficient capture of high-frequency phase aberration components,so we proposed a Principal-Component-Analysis-based method for representing phase aberrations.This paper discusses the factors influencing the accuracy of restoration,mainly including the sample space size and the sampling interval of D/r_(0),on the basis of characterizing phase aberrations by Principal Components(PCs).The experimental results show that a larger D/r_(0)sampling interval can ensure the generalization ability and robustness of the principal components in the case of a limited amount of original data,which can help to achieve high-precision deployment of the model in practical applications quickly.In the environment with relatively strong turbulence in the test set of D/r_(0)=24,the use of 34 terms of PCs can improve the corrected Strehl ratio(SR)from 0.007 to 0.1585,while the Strehl ratio of the light spot after restoration using 34 terms of ZPs is only 0.0215,demonstrating almost no correction effect.The results indicate that PCs can serve as a better alternative in representing and restoring the characteristics of atmospheric turbulence induced phase aberrations.These findings pave the way to use PCs of phase aberrations with fewer terms than traditional ZPs to achieve data dimensionality reduction,and offer a reference to accelerate and stabilize the model and deep learning based adaptive optics correction.
文摘Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.
文摘Dear Editor,Local recurrence and cervical lymph node metastases are major causes of mortality in patients with head and neck squamous cell carcinoma(HNSCC).To date,none of the proposed strategies for predicting outcomes in this disease have proven fully effective,and a comprehensive physical examination remains the primary method for early detection and monitoring of HNSCC.
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.
