The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass tran...The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass transition temperature,coefficient of thermal expansion,and cure shrinkage of materials.A simulation model of its curing deformation was established and validated against strain data obtained from fiber Bragg grating experiments.The effects of thickness,heating rate,and cooling rate on the curing temperature field and residual stress field during the molding of thick-section composite plates were analyzed.展开更多
The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)bi...The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)biopolymer to ameliorate residual granitic soil(RGS)in arid and semiarid regions can significantly mitigate soil erosion.This study investigates the enhancement of RGS by cross-linking the PBS and XG biopolymers.Employing a multitude of geotechnical tests(liquid limit,linear shrinkage,specific gravity,compaction,and UCS tests)at 3 d,28 d,and 90 d of steam-curing at a controlled temperature of 16℃,the outcomes were validated through scanning electron microscopy(SEM),thermogravimetric analysis(TGA),Fourier transform infrared spectroscopy(FTIR),and Brunauer-Emmett-Teller(BET)analyses.In addition,a comprehensive experimental database of 150 tests and nine parameters from the current study was utilized to model the UCS90-d(i.e.unconfined compressive strength after 90 d of curing)of the PBS-XG-treated RGS mixtures by deploying the random forest(RF)and eXtreme Gradient Boost(XGBoost)methods.The results found that the two biopolymers significantly improve the mechanical properties of RGS,with optimal UCS achieved at specific dosages(0.4PBS,1.5XG,and 0.2PBS+1.5XG dosage levels)and curing times.The UCS of PBS-XG-treated RGS showed up to a 57%increase after 90 d of curing.Furthermore,SEM and FTIR analyses revealed the formation of stronger microstructures and chemical bonds,respectively,whereas BET analysis indicated that pore volume and diameter are critical in affecting UCS.The proposed RF model outperformed XGBoost in predictive accuracy and generalization,demonstrating robustness and versatility.Moreover,SHAP values highlighted the significant impact of input parameters on UCS90-d,with curing time and specific material properties being key determinants.The study concludes with the proposal of a novel PyCharm intuitive graphical user interface as a"UCS Prediction App"for engineers and practitioners to forecast the UCS90-d of granitic residual soil.展开更多
In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At prese...In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.展开更多
Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that...Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.展开更多
BACKGROUND At present,the influencing factors of social function in patients with residual depressive symptoms are still unclear.Residual depressive symptoms are highly harmful,leading to low mood in patients,affectin...BACKGROUND At present,the influencing factors of social function in patients with residual depressive symptoms are still unclear.Residual depressive symptoms are highly harmful,leading to low mood in patients,affecting work and interpersonal communication,increasing the risk of recurrence,and adding to the burden on families.Studying the influencing factors of their social function is of great significance.AIM To explore the social function score and its influencing factors in patients with residual depressive symptoms.METHODS This observational study surveyed patients with residual depressive symptoms(case group)and healthy patients undergoing physical examinations(control group).Participants were admitted between January 2022 and December 2023.Social functioning was assessed using the Sheehan Disability Scale(SDS),and scores were compared between groups.Factors influencing SDS scores in patients with residual depressive symptoms were analyzed by applying multiple linear regression while using the receiver operating characteristic curve,and these RESULTS The SDS scores of the 158 patients with depressive symptoms were 11.48±3.26.Compared with the control group,the SDS scores and all items in the case group were higher.SDS scores were higher in patients with relapse,discon-tinuous medication,drug therapy alone,severe somatic symptoms,obvious residual symptoms,and anxiety scores≥8.Disease history,medication compliance,therapy method,and residual symptoms correlated positively with SDS scores(r=0.354,0.414,0.602,and 0.456,respectively).Independent influencing factors included disease history,medication compliance,therapy method,somatic symptoms,residual symptoms,and anxiety scores(P<0.05).The areas under the curve for predicting social functional impairment using these factors were 0.713,0.559,0.684,0.729,0.668,and 0.628,respectively,with sensitivities of 79.2%,61.8%,76.8%,81.7%,63.6%,and 65.5%and specificities of 83.3%,87.5%,82.6%,83.3%,86.7%,and 92.1%,respectively.CONCLUSION The social function scores of patients with residual symptoms of depression are high.They are affected by disease history,medication compliance,therapy method,degree of somatic symptoms,residual symptoms,and anxiety.展开更多
Producing steel requires large amounts of energy to convert iron ores into steel,which often comes from fossil fuels,leading to carbon emissions and other pollutants.Increasing scrap usage emerges as one of the most e...Producing steel requires large amounts of energy to convert iron ores into steel,which often comes from fossil fuels,leading to carbon emissions and other pollutants.Increasing scrap usage emerges as one of the most effective strategies for addressing these issues.However,typical residual elements(Cu,As,Sn,Sb,Bi,etc.)inherited from scrap could significantly influence the mechanical properties of steel.In this work,we investigate the effects of residual elements on the microstructure evolution and mechanical properties of a quenching and partitioning(Q&P)steel by comparing a commercial QP1180 steel(referred to as QP)to the one containing typical residual elements(Cu+As+Sn+Sb+Bi<0.3wt%)(referred to as QP-R).The results demonstrate that in comparison with the QP steel,the residual elements significantly refine the prior austenite grain(9.7μm vs.14.6μm)due to their strong solute drag effect,leading to a higher volume fraction(13.0%vs.11.8%),a smaller size(473 nm vs.790 nm)and a higher average carbon content(1.26 wt%vs.0.99 wt%)of retained austenite in the QP-R steel.As a result,the QP-R steel exhibits a sustained transformation-induced plasticity(TRIP)effect,leading to an enhanced strain hardening effect and a simultaneous improvement of strength and ductility.Grain boundary segregation of residual elements was not observed at prior austenite grain boundaries in the QP-R steel,primarily due to continuous interface migration during austenitization.This study demonstrates that the residual elements with concentrations comparable to that in scrap result in significant microstructural refinement,causing retained austenite with relatively higher stability and thus offering promising mechanical properties and potential applications.展开更多
Laser-welded Ti-6Al-4 V is prone to severe residual stresses,microstructural variation,and structural de-fects which are known detrimental to the mechanical properties of weld joints.Residual stress removal is typical...Laser-welded Ti-6Al-4 V is prone to severe residual stresses,microstructural variation,and structural de-fects which are known detrimental to the mechanical properties of weld joints.Residual stress removal is typically applied to weld joints for engineering purposes via heat treatment,in order to avoid prema-ture failure and performance degradation.In the present work,we found that proper welding residual stresses in laser-welded Ti-6Al-4 V sheets can maintain better ductility during uniaxial tension,as op-posed to the stress-relieved counterparts.A detailed experimental investigation has been performed on the deformation behaviours of Ti-6Al-4 V butt welds,including residual stress distribution characteriza-tions by focused ion beam ring-coring coupled with digital image correlation(FIB-DIC),X-ray comput-erized tomography(CT)for internal voids,and in-situ DIC analysis of the subregional strain evolutions.It was found that the pores preferentially distributed near the fusion zone(FZ)boundary,where the compressive residual stress was up to-330 MPa.The removal of residual stress resulted in a changed failure initiation site from the base material to the FZ boundary,the former with ductile and the latter with brittle fracture characteristics under tensile deformation.The combined effects of residual stresses,microstructures,and internal pores on the mechanical responses are discussed in detail.This work high-lights the importance of inevitable residual stress and pores in laser weld pieces,leading to key insights for post-welding treatment and service performance evaluations.展开更多
The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconci...The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconcile this contradiction,two Mg-0.1Sc-0.1Y-0.1Ag anodes with different residual strain distribution through extrusion with/without annealing are fabricated.The results indicate that annealing can significantly lessen the“pseudo-anode”regions,thereby changing the dissolution mode of the matrix and achieving an effective dissolution during discharge.Additionally,p-type semiconductor characteristic of discharge productfilm could suppress the self-corrosion reaction without reducing the polarization of anode.The magnesium-air battery utilizing annealed Mg-0.1Sc-0.1Y-0.1Ag as anode achieves a synergistic improvement in specific capacity(1388.89 mA h g^(-1))and energy density(1960.42 mW h g^(-1)).This anode modification method accelerates the advancement of high efficiency and long lifespan magnesium-air batteries,offering renewable and cost-effective energy solutions for electronics and emergency equipment.展开更多
This study investigates the effect of high current density electropulsing on the material in a rapid stress relaxation process.An AISI 1020 steel was shot-peened to induce surface compressive residual stresses in a co...This study investigates the effect of high current density electropulsing on the material in a rapid stress relaxation process.An AISI 1020 steel was shot-peened to induce surface compressive residual stresses in a controlled manner and subsequently electropulsed to investigate the changes in microstructure and defect configuration.AISI 1020 steel was chosen as it has a simple microstructure(plain ferritic)and composition with low alloying conditions.It is an appropriate material to study the effect of trans-mitting electric pulses on the microstructural defect evolution.A combination of electron-backscattered diffraction and transmission electron microscopy proved to be an effective tool in characterizing the post-electropulsing effects critically.By application of electropulsing,a reduction in the surface residual stress layer was noticed.Also,reductions in misorientation and dislocation density together with the disentan-glement of dislocations within the cold-worked layer were observed after electropulsing.Additionally,the annihilation of shot-peening-induced deformation bands beyond the residual layer depth was observed.These effects have been rationalised by taking into account the various possibilities of athermal effects of electropulsing.展开更多
7039 Al alloys are widely used in armor vehicles,given the material’s high specific strength and fracture toughness.However,laminar tearing in the thickness plane of the base metal(BM),specifically in the normal dire...7039 Al alloys are widely used in armor vehicles,given the material’s high specific strength and fracture toughness.However,laminar tearing in the thickness plane of the base metal(BM),specifically in the normal direction(ND)and rolling direction(RD)plane,was occasionally observed after the welding of thick plates,resulting in premature material failure.A vertically metal-inert gas(MIG)-welded laminar tearing component of a 30 mm thick plate was analyzed to determine the factors associated with this phenomenon.The texture,residual stress,microhardness,and tensile properties were also investigated.The results indicated that the crack extended along the RD as a transcrystalline fracture and terminated at the BM.The grains near the crack grew preferentially in the(001)crystal direction.Furthermore,the tensile strength(83 MPa)and elongation(6.8%)in the RD were relatively higher than those in the ND.In particular,the primary factors for crack initiation include stronger texture,higher dislocation density,increased Al_(7)Cu_(2)Fe phases,lower proportion of small-angle grain boundaries,and varying grain sizes in different regions,leading to the fragile microstructure.The higher residual stress of the BM promotes the formation and extension of cracks.The restraining force due to fixation and welding shrinkage force transformed the crack into laminar tearing.Preventive measures of laminar tearing were also proposed.展开更多
Abnormal network traffic, as a frequent security risk, requires a series of techniques to categorize and detect it. Existing network traffic anomaly detection still faces challenges: the inability to fully extract loc...Abnormal network traffic, as a frequent security risk, requires a series of techniques to categorize and detect it. Existing network traffic anomaly detection still faces challenges: the inability to fully extract local and global features, as well as the lack of effective mechanisms to capture complex interactions between features;Additionally, when increasing the receptive field to obtain deeper feature representations, the reliance on increasing network depth leads to a significant increase in computational resource consumption, affecting the efficiency and performance of detection. Based on these issues, firstly, this paper proposes a network traffic anomaly detection model based on parallel dilated convolution and residual learning (Res-PDC). To better explore the interactive relationships between features, the traffic samples are converted into two-dimensional matrix. A module combining parallel dilated convolutions and residual learning (res-pdc) was designed to extract local and global features of traffic at different scales. By utilizing res-pdc modules with different dilation rates, we can effectively capture spatial features at different scales and explore feature dependencies spanning wider regions without increasing computational resources. Secondly, to focus and integrate the information in different feature subspaces, further enhance and extract the interactions among the features, multi-head attention is added to Res-PDC, resulting in the final model: multi-head attention enhanced parallel dilated convolution and residual learning (MHA-Res-PDC) for network traffic anomaly detection. Finally, comparisons with other machine learning and deep learning algorithms are conducted on the NSL-KDD and CIC-IDS-2018 datasets. The experimental results demonstrate that the proposed method in this paper can effectively improve the detection performance.展开更多
This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline,integrating advanced numerical simulation with experim...This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline,integrating advanced numerical simulation with experimental validation.The research methodology incorporates three distinct parameter grouping approaches:a random group based on statistical analysis of 389 actual corrosion defects detected during 2023 MFL inspection,a deviation group representing historically documented failure scenarios,and a structural group examining systematic parameter variations.Using ABAQUS finite element software,we developed a dynamic implicit analysis model incorporating geometric nonlinearity and validated it through 1:12.7 scaled model testing,achieving prediction deviations consistently within 5%for standard cases.Our analysis revealed distinct failure mechanisms between large and small defects,with large defects exhibiting stress concentration at circumferential edges and small defects concentrating stress centrally.Quantitative analysis identified defect depth as themost significant factor,with every 1mmincrease reducing strength by 0.054MPa,while defect length showed moderate influence at 0.0018MPa reduction per mm.Comparative analysis demonstrated that circumferential defects exhibited 15%higher burst failure pressure compared to axial defects,though this advantage diminished significantly at depths exceeding 40%wall thickness.These findings,validated through experimental testing with deviations within 5%,provide valuable insights for pipeline integrity management,particularly emphasizing the importance of defect depth monitoring and the need for orientation-specific assessment criteria in corrosion evaluation protocols.展开更多
The MIG welding of in-situ generated nano-Al_(2)O_(3)powder metallurgy 7A52(PM 7A52)aluminum alloy was investigated.The microstructure was characterized using EBSD and TEM,while macrotexture and internal residual stre...The MIG welding of in-situ generated nano-Al_(2)O_(3)powder metallurgy 7A52(PM 7A52)aluminum alloy was investigated.The microstructure was characterized using EBSD and TEM,while macrotexture and internal residual stresses were analyzed with a self-developed SWXRD technique.The results revealed that PM 7A52 aluminum alloy effectively reduced the grain size,dislocation density,and texture strength in the post-weld microstructure.Furthermore,the residual stress in the weld zone(WZ)of PM 7A52 aluminum alloy was reduced by 38 MPa compared to that of the conventional melt-cast 7A52(CM 7A52)aluminum alloy.Notably,the tensile strength and elongation of welded joints in PM 7A52 aluminum alloy were increased by approximately 15%and 26%,respectively.The improvement in joint tensile strength was primarily attributed to grain boundary strengthening and dispersion strengthening caused byγ-Al_(2)O_(3)particles entering the WZ.展开更多
Rock residual strength,as an important input parameter,plays an indispensable role in proposing the reasonable and scientific scheme about stope design,underground tunnel excavation and stability evaluation of deep ch...Rock residual strength,as an important input parameter,plays an indispensable role in proposing the reasonable and scientific scheme about stope design,underground tunnel excavation and stability evaluation of deep chambers.Therefore,previous residual strength models of rocks established were reviewed.And corresponding related problems were stated.Subsequently,starting from the effects of bedding and whole life-cycle evolution process,series of triaxial mechanical tests of deep bedded sandstone with five bedding angles were conducted under different confining pressures.Then,six residual strength models considering the effects of bedding and whole life-cycle evolution process were established and evaluated.Finally,a cohesion loss model for determining residual strength of deep bedded sandstone was verified.The results showed that the effects of bedding and whole life-cycle evolution process had both significant influences on the evolution characteristic of residual strength of deep bedded sandstone.Additionally,residual strength parameters:residual cohesion and residual internal friction angle of deep bedded sandstone were not constant,which both significantly changed with increasing bedding angle.Besides,the cohesion loss model was the most suitable for determining and estimating the residual strength of bedded rocks,which could provide more accurate theoretical guidance for the stability control of deep chambers.展开更多
Electromagnetic interference,which necessitates the rapid advancement of substances with exceptional capabilities for bsorbing electromagnetic waves,is of urgent concern in contemporary society.In this work,CoFe_(2)O_...Electromagnetic interference,which necessitates the rapid advancement of substances with exceptional capabilities for bsorbing electromagnetic waves,is of urgent concern in contemporary society.In this work,CoFe_(2)O_(4)/residual carbon from coal gasification fine slag(CFO/RC)composites were created using a novel hydrothermal method.Various mechanisms for microwave absorption,including conductive loss,natural resonance,interfacial dipole polarization,and magnetic flux loss,are involved in these composites.Consequently,compared with pure residual carbon materials,this composite offers superior capabilities in microwave absorption.At 7.76GHz,the CFO/RC-2 composite achieves an impressive minimum reflection loss(RL_(min))of-43.99 dB with a thickness of 2.44 mm.Moreover,CFO/RC-3 demonstrates an effective absorption bandwidth(EAB)of up to 4.16 GHz,accompanied by a thickness of 1.18mm.This study revealed the remarkable capability of the composite to diminish electromagnetic waves,providing a new generation method for microwave absorbing materials of superior quality.展开更多
As service conditions become more challenging and production complexity increases,there is an increasing demand for enhanced comprehensive performance of ceramic/metal heterostructures.At present,brazing technique has...As service conditions become more challenging and production complexity increases,there is an increasing demand for enhanced comprehensive performance of ceramic/metal heterostructures.At present,brazing technique has been widely utilized for ceramic-metal heterogeneous joints.However,the residual stress relief in these welding joints is complicated and necessary.Because metals and ceramics have different properties,especially their coefficients of thermal expansion.Welding joints exhibit large residual stresses during the cooling process.The relatively high residual stresses may significantly degrade the joint properties.For this issue,four alleviation routes were reviewed:optimization of process parameters,setting an intermediate layer,surface structure modulation and particle-reinforced composite solder.The states and distribution patterns of residual stress in ceramic-metal brazed joints were summarized,and the generation and detection of residual stress were introduced.Eventually,upcoming prospects and challenges of residual stress research on ceramic/metal heterostructures were pointed out.展开更多
Objective N6-methyladenosine(m6A),the most prevalent epigenetic modification in eukaryotic RNA,plays a pivotal role in regulating cellular differentiation and developmental processes,with its dysregulation implicated ...Objective N6-methyladenosine(m6A),the most prevalent epigenetic modification in eukaryotic RNA,plays a pivotal role in regulating cellular differentiation and developmental processes,with its dysregulation implicated in diverse pathological conditions.Accurate prediction of m6A sites is critical for elucidating their regulatory mechanisms and informing drug development.However,traditional experimental methods are time-consuming and costly.Although various computational approaches have been proposed,challenges remain in feature learning,predictive accuracy,and generalization.Here,we present m6A-PSRA,a dual-branch residual-network-based predictor that fully exploits RNA sequence information to enhance prediction performance and model generalization.Methods m6A-PSRA adopts a parallel dual-branch network architecture to comprehensively extract RNA sequence features via two independent pathways.The first branch applies one-hot encoding to transform the RNA sequence into a numerical matrix while strictly preserving positional information and sequence continuity.This ensures that the biological context conveyed by nucleotide order is retained.A bidirectional long short-term memory network(BiLSTM)then processes the encoded matrix,capturing both forward and backward dependencies between bases to resolve contextual correlations.The second branch employs a k-mer tokenization strategy(k=3),decomposing the sequence into overlapping 3-mer subsequences to capture local sequence patterns.A pre-trained Doc2vec model maps these subsequences into fixeddimensional vectors,reducing feature dimensionality while extracting latent global semantic information via context learning.Both branches integrate residual networks(ResNet)and a self-attention mechanism:ResNet mitigates vanishing gradients through skip connections,preserving feature integrity,while self-attention adaptively assigns weights to focus on sequence regions most relevant to methylation prediction.This synergy enhances both feature learning and generalization capability.Results Across 11 tissues from humans,mice,and rats,m6A-PSRA consistently outperformed existing methods in accuracy(ACC)and area under the curve(AUC),achieving>90%ACC and>95%AUC in every tissue tested,indicating strong cross-species and cross-tissue adaptability.Validation on independent datasets—including three human cell lines(MOLM1,HEK293,A549)and a long-sequence dataset(m6A_IND,1001 nt)—confirmed stable performance across varied biological contexts and sequence lengths.Ablation studies demonstrated that the dual-branch architecture,residual network,and self-attention mechanism each contribute critically to performance,with their combination reducing interference between pathways.Motif analysis revealed an enrichment of m6A sites in guanine(G)and cytosine(C),consistent with known regulatory patterns,supporting the model’s biological plausibility.Conclusion m6A-PSRA effectively captures RNA sequence features,achieving high prediction accuracy and robust generalization across tissues and species,providing an efficient computational tool for m6A methylation site prediction.展开更多
Through a modified inherent strain model based on the minimum residual stress and deformation,three building schemes with different building postures and support structures were evaluated by finite element analysis.Re...Through a modified inherent strain model based on the minimum residual stress and deformation,three building schemes with different building postures and support structures were evaluated by finite element analysis.Results demonstrate that according to the principle of reducing the overall height of the building and reducing the support structure with a large tilt angle from the building direction,the residual stress and deformation can be effectively reduced by proper design of building posture and support before laser powder bed melting.Moreover,without the data of thermophysical property variation of Ti-6Al-4V artificial knee implants with temperature,predicting the residual stress and deformation with acceptable accuracy and reduced time cost can be achieved by the inherent strain model.展开更多
In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantl...In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12172045,U2241240,and 12221002)the National Program on Key Basic Research Project,China(Grant No.2019-JCJQ-ZD-308-00).
文摘The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass transition temperature,coefficient of thermal expansion,and cure shrinkage of materials.A simulation model of its curing deformation was established and validated against strain data obtained from fiber Bragg grating experiments.The effects of thickness,heating rate,and cooling rate on the curing temperature field and residual stress field during the molding of thick-section composite plates were analyzed.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379104 and 52090084).
文摘The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)biopolymer to ameliorate residual granitic soil(RGS)in arid and semiarid regions can significantly mitigate soil erosion.This study investigates the enhancement of RGS by cross-linking the PBS and XG biopolymers.Employing a multitude of geotechnical tests(liquid limit,linear shrinkage,specific gravity,compaction,and UCS tests)at 3 d,28 d,and 90 d of steam-curing at a controlled temperature of 16℃,the outcomes were validated through scanning electron microscopy(SEM),thermogravimetric analysis(TGA),Fourier transform infrared spectroscopy(FTIR),and Brunauer-Emmett-Teller(BET)analyses.In addition,a comprehensive experimental database of 150 tests and nine parameters from the current study was utilized to model the UCS90-d(i.e.unconfined compressive strength after 90 d of curing)of the PBS-XG-treated RGS mixtures by deploying the random forest(RF)and eXtreme Gradient Boost(XGBoost)methods.The results found that the two biopolymers significantly improve the mechanical properties of RGS,with optimal UCS achieved at specific dosages(0.4PBS,1.5XG,and 0.2PBS+1.5XG dosage levels)and curing times.The UCS of PBS-XG-treated RGS showed up to a 57%increase after 90 d of curing.Furthermore,SEM and FTIR analyses revealed the formation of stronger microstructures and chemical bonds,respectively,whereas BET analysis indicated that pore volume and diameter are critical in affecting UCS.The proposed RF model outperformed XGBoost in predictive accuracy and generalization,demonstrating robustness and versatility.Moreover,SHAP values highlighted the significant impact of input parameters on UCS90-d,with curing time and specific material properties being key determinants.The study concludes with the proposal of a novel PyCharm intuitive graphical user interface as a"UCS Prediction App"for engineers and practitioners to forecast the UCS90-d of granitic residual soil.
文摘In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.
基金supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI under Grant JP22H03643Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)under Grant JPMJSP2145JST through the Establishment of University Fellowships towards the Creation of Science Technology Innovation under Grant JPMJFS2115.
文摘Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.
文摘BACKGROUND At present,the influencing factors of social function in patients with residual depressive symptoms are still unclear.Residual depressive symptoms are highly harmful,leading to low mood in patients,affecting work and interpersonal communication,increasing the risk of recurrence,and adding to the burden on families.Studying the influencing factors of their social function is of great significance.AIM To explore the social function score and its influencing factors in patients with residual depressive symptoms.METHODS This observational study surveyed patients with residual depressive symptoms(case group)and healthy patients undergoing physical examinations(control group).Participants were admitted between January 2022 and December 2023.Social functioning was assessed using the Sheehan Disability Scale(SDS),and scores were compared between groups.Factors influencing SDS scores in patients with residual depressive symptoms were analyzed by applying multiple linear regression while using the receiver operating characteristic curve,and these RESULTS The SDS scores of the 158 patients with depressive symptoms were 11.48±3.26.Compared with the control group,the SDS scores and all items in the case group were higher.SDS scores were higher in patients with relapse,discon-tinuous medication,drug therapy alone,severe somatic symptoms,obvious residual symptoms,and anxiety scores≥8.Disease history,medication compliance,therapy method,and residual symptoms correlated positively with SDS scores(r=0.354,0.414,0.602,and 0.456,respectively).Independent influencing factors included disease history,medication compliance,therapy method,somatic symptoms,residual symptoms,and anxiety scores(P<0.05).The areas under the curve for predicting social functional impairment using these factors were 0.713,0.559,0.684,0.729,0.668,and 0.628,respectively,with sensitivities of 79.2%,61.8%,76.8%,81.7%,63.6%,and 65.5%and specificities of 83.3%,87.5%,82.6%,83.3%,86.7%,and 92.1%,respectively.CONCLUSION The social function scores of patients with residual symptoms of depression are high.They are affected by disease history,medication compliance,therapy method,degree of somatic symptoms,residual symptoms,and anxiety.
基金financially supported by the National Natural Science Foundation of China(Nos.52293395 and 52293393)the Xiongan Science and Technology Innovation Talent Project of MOST,China(No.2022XACX0500).
文摘Producing steel requires large amounts of energy to convert iron ores into steel,which often comes from fossil fuels,leading to carbon emissions and other pollutants.Increasing scrap usage emerges as one of the most effective strategies for addressing these issues.However,typical residual elements(Cu,As,Sn,Sb,Bi,etc.)inherited from scrap could significantly influence the mechanical properties of steel.In this work,we investigate the effects of residual elements on the microstructure evolution and mechanical properties of a quenching and partitioning(Q&P)steel by comparing a commercial QP1180 steel(referred to as QP)to the one containing typical residual elements(Cu+As+Sn+Sb+Bi<0.3wt%)(referred to as QP-R).The results demonstrate that in comparison with the QP steel,the residual elements significantly refine the prior austenite grain(9.7μm vs.14.6μm)due to their strong solute drag effect,leading to a higher volume fraction(13.0%vs.11.8%),a smaller size(473 nm vs.790 nm)and a higher average carbon content(1.26 wt%vs.0.99 wt%)of retained austenite in the QP-R steel.As a result,the QP-R steel exhibits a sustained transformation-induced plasticity(TRIP)effect,leading to an enhanced strain hardening effect and a simultaneous improvement of strength and ductility.Grain boundary segregation of residual elements was not observed at prior austenite grain boundaries in the QP-R steel,primarily due to continuous interface migration during austenitization.This study demonstrates that the residual elements with concentrations comparable to that in scrap result in significant microstructural refinement,causing retained austenite with relatively higher stability and thus offering promising mechanical properties and potential applications.
基金supported by the National Key Re-search&Development Plan of China(No.2020YFA0405900)the Major Research Plan of the National Natural Science Foundation of China(No.92263201)Y.P.Xia would like to thank the support by the Jiangsu Funding Program for Excellent Postdoctoral Talent.All authors thank the Advanced Material Research Institute of Jiangsu Industrial Technology Research Institute(JITRI,Suzhou,China)for the experimental support.
文摘Laser-welded Ti-6Al-4 V is prone to severe residual stresses,microstructural variation,and structural de-fects which are known detrimental to the mechanical properties of weld joints.Residual stress removal is typically applied to weld joints for engineering purposes via heat treatment,in order to avoid prema-ture failure and performance degradation.In the present work,we found that proper welding residual stresses in laser-welded Ti-6Al-4 V sheets can maintain better ductility during uniaxial tension,as op-posed to the stress-relieved counterparts.A detailed experimental investigation has been performed on the deformation behaviours of Ti-6Al-4 V butt welds,including residual stress distribution characteriza-tions by focused ion beam ring-coring coupled with digital image correlation(FIB-DIC),X-ray comput-erized tomography(CT)for internal voids,and in-situ DIC analysis of the subregional strain evolutions.It was found that the pores preferentially distributed near the fusion zone(FZ)boundary,where the compressive residual stress was up to-330 MPa.The removal of residual stress resulted in a changed failure initiation site from the base material to the FZ boundary,the former with ductile and the latter with brittle fracture characteristics under tensile deformation.The combined effects of residual stresses,microstructures,and internal pores on the mechanical responses are discussed in detail.This work high-lights the importance of inevitable residual stress and pores in laser weld pieces,leading to key insights for post-welding treatment and service performance evaluations.
基金the National Natural Science:Foundation of China(52375370)the Open Project of Salt Lake Chemical Engineering Research Complex,Qinghai University(2023-DXSSKF-Z02)+2 种基金the Nat-ural Science Foundation of Shanxi(202103021224049)GDAS Projects of International cooperation platform of Sci-ence and Technology(2022GDASZH-2022010203-003)Guangdong province Science and Technology Plan Projects(2023B1212060045).
文摘The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconcile this contradiction,two Mg-0.1Sc-0.1Y-0.1Ag anodes with different residual strain distribution through extrusion with/without annealing are fabricated.The results indicate that annealing can significantly lessen the“pseudo-anode”regions,thereby changing the dissolution mode of the matrix and achieving an effective dissolution during discharge.Additionally,p-type semiconductor characteristic of discharge productfilm could suppress the self-corrosion reaction without reducing the polarization of anode.The magnesium-air battery utilizing annealed Mg-0.1Sc-0.1Y-0.1Ag as anode achieves a synergistic improvement in specific capacity(1388.89 mA h g^(-1))and energy density(1960.42 mW h g^(-1)).This anode modification method accelerates the advancement of high efficiency and long lifespan magnesium-air batteries,offering renewable and cost-effective energy solutions for electronics and emergency equipment.
基金supported by the National Research Foundation of Singapore,Rolls-Royce Singapore Pte.Ltd.,and Nanyang Technological University through grants#002123-00009 and #002124-00009.
文摘This study investigates the effect of high current density electropulsing on the material in a rapid stress relaxation process.An AISI 1020 steel was shot-peened to induce surface compressive residual stresses in a controlled manner and subsequently electropulsed to investigate the changes in microstructure and defect configuration.AISI 1020 steel was chosen as it has a simple microstructure(plain ferritic)and composition with low alloying conditions.It is an appropriate material to study the effect of trans-mitting electric pulses on the microstructural defect evolution.A combination of electron-backscattered diffraction and transmission electron microscopy proved to be an effective tool in characterizing the post-electropulsing effects critically.By application of electropulsing,a reduction in the surface residual stress layer was noticed.Also,reductions in misorientation and dislocation density together with the disentan-glement of dislocations within the cold-worked layer were observed after electropulsing.Additionally,the annihilation of shot-peening-induced deformation bands beyond the residual layer depth was observed.These effects have been rationalised by taking into account the various possibilities of athermal effects of electropulsing.
基金supported by the National Key Research and Development Program of China(No.SQ2021YFF 0600011).
文摘7039 Al alloys are widely used in armor vehicles,given the material’s high specific strength and fracture toughness.However,laminar tearing in the thickness plane of the base metal(BM),specifically in the normal direction(ND)and rolling direction(RD)plane,was occasionally observed after the welding of thick plates,resulting in premature material failure.A vertically metal-inert gas(MIG)-welded laminar tearing component of a 30 mm thick plate was analyzed to determine the factors associated with this phenomenon.The texture,residual stress,microhardness,and tensile properties were also investigated.The results indicated that the crack extended along the RD as a transcrystalline fracture and terminated at the BM.The grains near the crack grew preferentially in the(001)crystal direction.Furthermore,the tensile strength(83 MPa)and elongation(6.8%)in the RD were relatively higher than those in the ND.In particular,the primary factors for crack initiation include stronger texture,higher dislocation density,increased Al_(7)Cu_(2)Fe phases,lower proportion of small-angle grain boundaries,and varying grain sizes in different regions,leading to the fragile microstructure.The higher residual stress of the BM promotes the formation and extension of cracks.The restraining force due to fixation and welding shrinkage force transformed the crack into laminar tearing.Preventive measures of laminar tearing were also proposed.
基金supported by the Xiamen Science and Technology Subsidy Project(No.2023CXY0318).
文摘Abnormal network traffic, as a frequent security risk, requires a series of techniques to categorize and detect it. Existing network traffic anomaly detection still faces challenges: the inability to fully extract local and global features, as well as the lack of effective mechanisms to capture complex interactions between features;Additionally, when increasing the receptive field to obtain deeper feature representations, the reliance on increasing network depth leads to a significant increase in computational resource consumption, affecting the efficiency and performance of detection. Based on these issues, firstly, this paper proposes a network traffic anomaly detection model based on parallel dilated convolution and residual learning (Res-PDC). To better explore the interactive relationships between features, the traffic samples are converted into two-dimensional matrix. A module combining parallel dilated convolutions and residual learning (res-pdc) was designed to extract local and global features of traffic at different scales. By utilizing res-pdc modules with different dilation rates, we can effectively capture spatial features at different scales and explore feature dependencies spanning wider regions without increasing computational resources. Secondly, to focus and integrate the information in different feature subspaces, further enhance and extract the interactions among the features, multi-head attention is added to Res-PDC, resulting in the final model: multi-head attention enhanced parallel dilated convolution and residual learning (MHA-Res-PDC) for network traffic anomaly detection. Finally, comparisons with other machine learning and deep learning algorithms are conducted on the NSL-KDD and CIC-IDS-2018 datasets. The experimental results demonstrate that the proposed method in this paper can effectively improve the detection performance.
文摘This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline,integrating advanced numerical simulation with experimental validation.The research methodology incorporates three distinct parameter grouping approaches:a random group based on statistical analysis of 389 actual corrosion defects detected during 2023 MFL inspection,a deviation group representing historically documented failure scenarios,and a structural group examining systematic parameter variations.Using ABAQUS finite element software,we developed a dynamic implicit analysis model incorporating geometric nonlinearity and validated it through 1:12.7 scaled model testing,achieving prediction deviations consistently within 5%for standard cases.Our analysis revealed distinct failure mechanisms between large and small defects,with large defects exhibiting stress concentration at circumferential edges and small defects concentrating stress centrally.Quantitative analysis identified defect depth as themost significant factor,with every 1mmincrease reducing strength by 0.054MPa,while defect length showed moderate influence at 0.0018MPa reduction per mm.Comparative analysis demonstrated that circumferential defects exhibited 15%higher burst failure pressure compared to axial defects,though this advantage diminished significantly at depths exceeding 40%wall thickness.These findings,validated through experimental testing with deviations within 5%,provide valuable insights for pipeline integrity management,particularly emphasizing the importance of defect depth monitoring and the need for orientation-specific assessment criteria in corrosion evaluation protocols.
基金supported by the National Key Research and Development Program of China(No.SQ2021YFF0600011)。
文摘The MIG welding of in-situ generated nano-Al_(2)O_(3)powder metallurgy 7A52(PM 7A52)aluminum alloy was investigated.The microstructure was characterized using EBSD and TEM,while macrotexture and internal residual stresses were analyzed with a self-developed SWXRD technique.The results revealed that PM 7A52 aluminum alloy effectively reduced the grain size,dislocation density,and texture strength in the post-weld microstructure.Furthermore,the residual stress in the weld zone(WZ)of PM 7A52 aluminum alloy was reduced by 38 MPa compared to that of the conventional melt-cast 7A52(CM 7A52)aluminum alloy.Notably,the tensile strength and elongation of welded joints in PM 7A52 aluminum alloy were increased by approximately 15%and 26%,respectively.The improvement in joint tensile strength was primarily attributed to grain boundary strengthening and dispersion strengthening caused byγ-Al_(2)O_(3)particles entering the WZ.
基金Projects(2024YFC3013801,2022YFC3004602)supported by the National Key R&D Program of ChinaProjects(U23B2093,52034009)supported by the National Natural Science Foundation of China。
文摘Rock residual strength,as an important input parameter,plays an indispensable role in proposing the reasonable and scientific scheme about stope design,underground tunnel excavation and stability evaluation of deep chambers.Therefore,previous residual strength models of rocks established were reviewed.And corresponding related problems were stated.Subsequently,starting from the effects of bedding and whole life-cycle evolution process,series of triaxial mechanical tests of deep bedded sandstone with five bedding angles were conducted under different confining pressures.Then,six residual strength models considering the effects of bedding and whole life-cycle evolution process were established and evaluated.Finally,a cohesion loss model for determining residual strength of deep bedded sandstone was verified.The results showed that the effects of bedding and whole life-cycle evolution process had both significant influences on the evolution characteristic of residual strength of deep bedded sandstone.Additionally,residual strength parameters:residual cohesion and residual internal friction angle of deep bedded sandstone were not constant,which both significantly changed with increasing bedding angle.Besides,the cohesion loss model was the most suitable for determining and estimating the residual strength of bedded rocks,which could provide more accurate theoretical guidance for the stability control of deep chambers.
基金financially supported by the Key Project of Natural Science Research in Colleges and Universities of Anhui Province,China(No.2022AH050816)the Open Research Grant of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining(Nos.EC2023013 and EC2022018)+1 种基金the National Natural Science Foundation of China(No.52200139)the Introduction of Talent in Anhui University of Science and Technology,China(Nos.2021yjrc18 and 2023yjrc79)。
文摘Electromagnetic interference,which necessitates the rapid advancement of substances with exceptional capabilities for bsorbing electromagnetic waves,is of urgent concern in contemporary society.In this work,CoFe_(2)O_(4)/residual carbon from coal gasification fine slag(CFO/RC)composites were created using a novel hydrothermal method.Various mechanisms for microwave absorption,including conductive loss,natural resonance,interfacial dipole polarization,and magnetic flux loss,are involved in these composites.Consequently,compared with pure residual carbon materials,this composite offers superior capabilities in microwave absorption.At 7.76GHz,the CFO/RC-2 composite achieves an impressive minimum reflection loss(RL_(min))of-43.99 dB with a thickness of 2.44 mm.Moreover,CFO/RC-3 demonstrates an effective absorption bandwidth(EAB)of up to 4.16 GHz,accompanied by a thickness of 1.18mm.This study revealed the remarkable capability of the composite to diminish electromagnetic waves,providing a new generation method for microwave absorbing materials of superior quality.
基金National Program of Foreign Experts of China(G2023026003L)National Natural Science Foundation of China(52475347)+4 种基金Postdoctoral Fund(2023M740475)International Science and Technology Cooperation Project of Henan Province(242102521057)Frontier Exploration Projects of Longmen Laboratory(LMQYTSKT016)Central Plains Science and Technology Innovation Leading TalentsProvincial Science and Technology R&D Program Joint Fund Projects(235200810030)。
文摘As service conditions become more challenging and production complexity increases,there is an increasing demand for enhanced comprehensive performance of ceramic/metal heterostructures.At present,brazing technique has been widely utilized for ceramic-metal heterogeneous joints.However,the residual stress relief in these welding joints is complicated and necessary.Because metals and ceramics have different properties,especially their coefficients of thermal expansion.Welding joints exhibit large residual stresses during the cooling process.The relatively high residual stresses may significantly degrade the joint properties.For this issue,four alleviation routes were reviewed:optimization of process parameters,setting an intermediate layer,surface structure modulation and particle-reinforced composite solder.The states and distribution patterns of residual stress in ceramic-metal brazed joints were summarized,and the generation and detection of residual stress were introduced.Eventually,upcoming prospects and challenges of residual stress research on ceramic/metal heterostructures were pointed out.
基金supported by grants from The National Natural Science Foundation of China(12361104)Yunnan Fundamental Research Projects(202301AT070016,202401AT070036)+2 种基金the Youth Talent Program of Xingdian Talent Support Plan(XDYC-QNRC-2022-0514)the Yunnan Province International Joint Laboratory for Intelligent Integration and Application of Ethnic Multilingualism(202403AP140014)the Open Research Fund of Yunnan Key Laboratory of Statistical Modeling and Data Analysis,Yunnan University(SMDAYB2023004)。
文摘Objective N6-methyladenosine(m6A),the most prevalent epigenetic modification in eukaryotic RNA,plays a pivotal role in regulating cellular differentiation and developmental processes,with its dysregulation implicated in diverse pathological conditions.Accurate prediction of m6A sites is critical for elucidating their regulatory mechanisms and informing drug development.However,traditional experimental methods are time-consuming and costly.Although various computational approaches have been proposed,challenges remain in feature learning,predictive accuracy,and generalization.Here,we present m6A-PSRA,a dual-branch residual-network-based predictor that fully exploits RNA sequence information to enhance prediction performance and model generalization.Methods m6A-PSRA adopts a parallel dual-branch network architecture to comprehensively extract RNA sequence features via two independent pathways.The first branch applies one-hot encoding to transform the RNA sequence into a numerical matrix while strictly preserving positional information and sequence continuity.This ensures that the biological context conveyed by nucleotide order is retained.A bidirectional long short-term memory network(BiLSTM)then processes the encoded matrix,capturing both forward and backward dependencies between bases to resolve contextual correlations.The second branch employs a k-mer tokenization strategy(k=3),decomposing the sequence into overlapping 3-mer subsequences to capture local sequence patterns.A pre-trained Doc2vec model maps these subsequences into fixeddimensional vectors,reducing feature dimensionality while extracting latent global semantic information via context learning.Both branches integrate residual networks(ResNet)and a self-attention mechanism:ResNet mitigates vanishing gradients through skip connections,preserving feature integrity,while self-attention adaptively assigns weights to focus on sequence regions most relevant to methylation prediction.This synergy enhances both feature learning and generalization capability.Results Across 11 tissues from humans,mice,and rats,m6A-PSRA consistently outperformed existing methods in accuracy(ACC)and area under the curve(AUC),achieving>90%ACC and>95%AUC in every tissue tested,indicating strong cross-species and cross-tissue adaptability.Validation on independent datasets—including three human cell lines(MOLM1,HEK293,A549)and a long-sequence dataset(m6A_IND,1001 nt)—confirmed stable performance across varied biological contexts and sequence lengths.Ablation studies demonstrated that the dual-branch architecture,residual network,and self-attention mechanism each contribute critically to performance,with their combination reducing interference between pathways.Motif analysis revealed an enrichment of m6A sites in guanine(G)and cytosine(C),consistent with known regulatory patterns,supporting the model’s biological plausibility.Conclusion m6A-PSRA effectively captures RNA sequence features,achieving high prediction accuracy and robust generalization across tissues and species,providing an efficient computational tool for m6A methylation site prediction.
基金Natural Science Foundation of Shandong Province(ZR2020ME020)。
文摘Through a modified inherent strain model based on the minimum residual stress and deformation,three building schemes with different building postures and support structures were evaluated by finite element analysis.Results demonstrate that according to the principle of reducing the overall height of the building and reducing the support structure with a large tilt angle from the building direction,the residual stress and deformation can be effectively reduced by proper design of building posture and support before laser powder bed melting.Moreover,without the data of thermophysical property variation of Ti-6Al-4V artificial knee implants with temperature,predicting the residual stress and deformation with acceptable accuracy and reduced time cost can be achieved by the inherent strain model.
文摘In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.
