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
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
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
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small targe...Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.展开更多
A healthy brain is vital to every person since the brain controls every movement and emotion.Sometimes,some brain cells grow unexpectedly to be uncontrollable and cancerous.These cancerous cells are called brain tumor...A healthy brain is vital to every person since the brain controls every movement and emotion.Sometimes,some brain cells grow unexpectedly to be uncontrollable and cancerous.These cancerous cells are called brain tumors.For diagnosed patients,their lives depend mainly on the early diagnosis of these tumors to provide suitable treatment plans.Nowadays,Physicians and radiologists rely on Magnetic Resonance Imaging(MRI)pictures for their clinical evaluations of brain tumors.These evaluations are time-consuming,expensive,and require expertise with high skills to provide an accurate diagnosis.Scholars and industrials have recently partnered to implement automatic solutions to diagnose the disease with high accuracy.Due to their accuracy,some of these solutions depend on deep-learning(DL)methodologies.These techniques have become important due to their roles in the diagnosis process,which includes identification and classification.Therefore,there is a need for a solid and robust approach based on a deep-learning method to diagnose brain tumors.The purpose of this study is to develop an intelligent automatic framework for brain tumor diagnosis.The proposed solution is based on a novel dense dynamic residual self-attention transfer adaptive learning fusion approach(NDDRSATALFA),carried over two implemented deep-learning networks:VGG19 and UNET to identify and classify brain tumors.In addition,this solution applies a transfer learning approach to exchange extracted features and data within the two neural networks.The presented framework is trained,validated,and tested on six public datasets of MRIs to detect brain tumors and categorize these tumors into three suitable classes,which are glioma,meningioma,and pituitary.The proposed framework yielded remarkable findings on variously evaluated performance indicators:99.32%accuracy,98.74%sensitivity,98.89%specificity,99.01%Dice,98.93%Area Under the Curve(AUC),and 99.81%F1-score.In addition,a comparative analysis with recent state-of-the-art methods was performed and according to the comparative analysis,NDDRSATALFA shows an admirable level of reliability in simplifying the timely identification of diverse brain tumors.Moreover,this framework can be applied by healthcare providers to assist radiologists,pathologists,and physicians in their evaluations.The attained outcomes open doors for advanced automatic solutions that improve clinical evaluations and provide reasonable treatment plans.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
Correction:J Cotton Res 8,27(2025)https://doi.org/10.1186/s42397-025-00228-y During the publication process of the original article(Soltani Toularoud et al.2025),the article title has been wrongly captured.Te article ...Correction:J Cotton Res 8,27(2025)https://doi.org/10.1186/s42397-025-00228-y During the publication process of the original article(Soltani Toularoud et al.2025),the article title has been wrongly captured.Te article title should be corrected from:of butisanstar and clopyralid herbicides on Gos-sypium hirsutum L.growth:insights from a pot experiment to:Residual efects of butisanstar and clopyralid herbi-cides on Gossypium hirsutum L.growth:insights from a pot experiment Te original article(Soltani Toularoud et al.2025)has been updated.Te publisher apologizes to the authors and readers for the inconvenience caused.展开更多
Background:Residual force enhancement(rFE),defined as increased isometric force following active lengthening compared to a fixed-end isometric contraction at the same muscle length and level of activation,is present a...Background:Residual force enhancement(rFE),defined as increased isometric force following active lengthening compared to a fixed-end isometric contraction at the same muscle length and level of activation,is present across all scales of muscle.While rFE is always present at the cellular level,often rFE"non-re sponders"are observed during joint-level voluntary contractions.Methods:We compared rFE between the joint level and single fiber level(vastus lateralis biopsies)in 16 young males.In vivo voluntary kneeextensor rFE was measured by comparing steady-state isometric torque between a stretch-hold(maximal activation at 150°,stretch to 70°,hold)and a fixed-end isometric contraction,with ultrasonographic recording of vastus lateralis fascicle length(FL).Fixed-end contractions were performed at 67.5°,70.0°,72.5°,and 75.0°;the joint angle that most closely matched FL of the stretch-hold contraction's isometric steady-state was used to calculate rFE.The starting and ending FLs of the stretch-hold contraction were expressed as%optimal FL,determined via torqueangle relationship.Resu lts:In single fiber experiments,the starting and ending fiber lengths were matched relative to optimal length determined from in vivo testing,yielding an average sarcomere excursion of~2.2-3.4μm.There was a greater magnitude of rFE at the single fiber(~20%)than joint level(~5%)(p=0.004),with"non-re sponders"only observed at the joint level.Conclusion:By comparing rFE across scales within the same participants,we show the development of the rFE non-responder phenomenon is upstream of rFE's cellular mechanisms,with rFE only lost rather than gained when scaling from single fibers to the joint level.展开更多
This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded cond...This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded condition,P91 steel welds primarily consist of untempered martensite,which transforms into tempered martensite during post-weld heat treatment(PWHT).Electron spectro-scopy analysis reveals the presence of M_(23)C_(6) and MX carbonitride precipitates at grain boundaries.Increasing the heat input leads to greater quantities of precipitates in the prior austenite grain boundaries,which can affect material properties.Weldment hardness profiles exhibit modest improvements,while ultimate tensile strength and toughness decrease with higher welding heat input,poten-tially due to the formation of a ferritic phase.Residual stress distributions are noticeably influenced by the welding heat input level.展开更多
In the burgeoning field of anomaly detection within attributed networks,traditional methodologies often encounter the intricacies of network complexity,particularly in capturing nonlinearity and sparsity.This study in...In the burgeoning field of anomaly detection within attributed networks,traditional methodologies often encounter the intricacies of network complexity,particularly in capturing nonlinearity and sparsity.This study introduces an innovative approach that synergizes the strengths of graph convolutional networks with advanced deep residual learning and a unique residual-based attention mechanism,thereby creating a more nuanced and efficient method for anomaly detection in complex networks.The heart of our model lies in the integration of graph convolutional networks that capture complex structural relationships within the network data.This is further bolstered by deep residual learning,which is employed to model intricate nonlinear connections directly from input data.A pivotal innovation in our approach is the incorporation of a residual-based attention mech-anism.This mechanism dynamically adjusts the importance of nodes based on their residual information,thereby significantly enhancing the sensitivity of the model to subtle anomalies.Furthermore,we introduce a novel hypersphere mapping technique in the latent space to distinctly separate normal and anomalous data.This mapping is the key to our model’s ability to pinpoint anomalies with greater precision.An extensive experimental setup was used to validate the efficacy of the proposed model.Using attributed social network datasets,we demonstrate that our model not only competes with but also surpasses existing state-of-the-art methods in anomaly detection.The results show the exceptional capability of our model to handle the multifaceted nature of real-world networks.展开更多
Granite residual soil slope is often destroyed,which poses great threats to Rong County in southeastern Guangxi,China.Heavy rainfall and fissures are the major triggering and internal factors.The fissure that controls...Granite residual soil slope is often destroyed,which poses great threats to Rong County in southeastern Guangxi,China.Heavy rainfall and fissures are the major triggering and internal factors.The fissure that controls the slope stability and the associated failure mechanisms remain unclear.The purpose of this study was to identify the controlling fissures through field investigation,elucidate the effect of its position,and analyze the failure process and hydrological response of residual soil slope through artificial flume model tests.The results comprised five aspects.(1)Surface weathering and unloading fissures could affect slope stability.(2)The failure processes with different fissure positions exhibited inconsistent characteristics.(3)The volume moisture content(VMC)had the most direct response at the fissure tip.The corresponding infiltration rate was the highest.The response time of pore water pressure(PWP)was longer than that of VMC.Fluctuations in PWP were associated with VMC and changes in the soil microstructure due to local deformation.(4)Slope failure was accompanied by serious soil erosion.This could be attributed to the infiltration direction and the interaction between soil and water.(5)Fissured soil slopes experienced five similar failure processes:sheet erosion and partial failure of the slope foot,occurrence of preferential flow and enlargement of the sliding area,creep deformation and tension fissure emergence,block sliding and gully erosion,and flow-slip.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
The study aimed to address the issue of elevated residual stress levels in dissimilar girth welds of cast steel joints.To achieve this,the hybrid welding technology,which yields high welding speeds while simultaneousl...The study aimed to address the issue of elevated residual stress levels in dissimilar girth welds of cast steel joints.To achieve this,the hybrid welding technology,which yields high welding speeds while simultaneously reducing residual stresses,has been introduced.This study utilizes a numerical simulation method to investigate the temperature and residual stress field in the hybrid welding of G20Mn5 casting-Q355 low-alloy steel welded pipe.A com-parison of the findings of this study with those of other welding processes revealed the technological advantages of hybrid welding.The research outcomes show that due to geometric discontinuities and material differences,the temperature field of the joint exhibits uneven distribution characteristics,and the peak temperatures on the Q355 steel side exceeds those on the G20Mn5 steel side.An evident stress gra-dient is present in the residual stress field of the joint post-welding,with peak stress located at the weld root on the Q355 steel.Compared with arc welding,the hybrid welding leads to decreased residual stresses and deformation,with high stress outside the heat-affected zone diminishing rapidly.Furthermore,it significantly improves the welding efficiency.This study elucidates the distribution and underlying causes of thermal and residual stress fields in dissimilar girth welds.This serves as a foundation for the application of hybrid welding technology in welded cast steel joints.展开更多
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.
基金Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202)。
文摘Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.(GPIP:1055-829-2024).
文摘A healthy brain is vital to every person since the brain controls every movement and emotion.Sometimes,some brain cells grow unexpectedly to be uncontrollable and cancerous.These cancerous cells are called brain tumors.For diagnosed patients,their lives depend mainly on the early diagnosis of these tumors to provide suitable treatment plans.Nowadays,Physicians and radiologists rely on Magnetic Resonance Imaging(MRI)pictures for their clinical evaluations of brain tumors.These evaluations are time-consuming,expensive,and require expertise with high skills to provide an accurate diagnosis.Scholars and industrials have recently partnered to implement automatic solutions to diagnose the disease with high accuracy.Due to their accuracy,some of these solutions depend on deep-learning(DL)methodologies.These techniques have become important due to their roles in the diagnosis process,which includes identification and classification.Therefore,there is a need for a solid and robust approach based on a deep-learning method to diagnose brain tumors.The purpose of this study is to develop an intelligent automatic framework for brain tumor diagnosis.The proposed solution is based on a novel dense dynamic residual self-attention transfer adaptive learning fusion approach(NDDRSATALFA),carried over two implemented deep-learning networks:VGG19 and UNET to identify and classify brain tumors.In addition,this solution applies a transfer learning approach to exchange extracted features and data within the two neural networks.The presented framework is trained,validated,and tested on six public datasets of MRIs to detect brain tumors and categorize these tumors into three suitable classes,which are glioma,meningioma,and pituitary.The proposed framework yielded remarkable findings on variously evaluated performance indicators:99.32%accuracy,98.74%sensitivity,98.89%specificity,99.01%Dice,98.93%Area Under the Curve(AUC),and 99.81%F1-score.In addition,a comparative analysis with recent state-of-the-art methods was performed and according to the comparative analysis,NDDRSATALFA shows an admirable level of reliability in simplifying the timely identification of diverse brain tumors.Moreover,this framework can be applied by healthcare providers to assist radiologists,pathologists,and physicians in their evaluations.The attained outcomes open doors for advanced automatic solutions that improve clinical evaluations and provide reasonable treatment plans.
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.
文摘Correction:J Cotton Res 8,27(2025)https://doi.org/10.1186/s42397-025-00228-y During the publication process of the original article(Soltani Toularoud et al.2025),the article title has been wrongly captured.Te article title should be corrected from:of butisanstar and clopyralid herbicides on Gos-sypium hirsutum L.growth:insights from a pot experiment to:Residual efects of butisanstar and clopyralid herbi-cides on Gossypium hirsutum L.growth:insights from a pot experiment Te original article(Soltani Toularoud et al.2025)has been updated.Te publisher apologizes to the authors and readers for the inconvenience caused.
基金supported by the Natural Sciences and Engineering Research Council of Canada(NSERC,Grant No.RGPIN-2024-03782).
文摘Background:Residual force enhancement(rFE),defined as increased isometric force following active lengthening compared to a fixed-end isometric contraction at the same muscle length and level of activation,is present across all scales of muscle.While rFE is always present at the cellular level,often rFE"non-re sponders"are observed during joint-level voluntary contractions.Methods:We compared rFE between the joint level and single fiber level(vastus lateralis biopsies)in 16 young males.In vivo voluntary kneeextensor rFE was measured by comparing steady-state isometric torque between a stretch-hold(maximal activation at 150°,stretch to 70°,hold)and a fixed-end isometric contraction,with ultrasonographic recording of vastus lateralis fascicle length(FL).Fixed-end contractions were performed at 67.5°,70.0°,72.5°,and 75.0°;the joint angle that most closely matched FL of the stretch-hold contraction's isometric steady-state was used to calculate rFE.The starting and ending FLs of the stretch-hold contraction were expressed as%optimal FL,determined via torqueangle relationship.Resu lts:In single fiber experiments,the starting and ending fiber lengths were matched relative to optimal length determined from in vivo testing,yielding an average sarcomere excursion of~2.2-3.4μm.There was a greater magnitude of rFE at the single fiber(~20%)than joint level(~5%)(p=0.004),with"non-re sponders"only observed at the joint level.Conclusion:By comparing rFE across scales within the same participants,we show the development of the rFE non-responder phenomenon is upstream of rFE's cellular mechanisms,with rFE only lost rather than gained when scaling from single fibers to the joint level.
文摘This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded condition,P91 steel welds primarily consist of untempered martensite,which transforms into tempered martensite during post-weld heat treatment(PWHT).Electron spectro-scopy analysis reveals the presence of M_(23)C_(6) and MX carbonitride precipitates at grain boundaries.Increasing the heat input leads to greater quantities of precipitates in the prior austenite grain boundaries,which can affect material properties.Weldment hardness profiles exhibit modest improvements,while ultimate tensile strength and toughness decrease with higher welding heat input,poten-tially due to the formation of a ferritic phase.Residual stress distributions are noticeably influenced by the welding heat input level.
文摘In the burgeoning field of anomaly detection within attributed networks,traditional methodologies often encounter the intricacies of network complexity,particularly in capturing nonlinearity and sparsity.This study introduces an innovative approach that synergizes the strengths of graph convolutional networks with advanced deep residual learning and a unique residual-based attention mechanism,thereby creating a more nuanced and efficient method for anomaly detection in complex networks.The heart of our model lies in the integration of graph convolutional networks that capture complex structural relationships within the network data.This is further bolstered by deep residual learning,which is employed to model intricate nonlinear connections directly from input data.A pivotal innovation in our approach is the incorporation of a residual-based attention mech-anism.This mechanism dynamically adjusts the importance of nodes based on their residual information,thereby significantly enhancing the sensitivity of the model to subtle anomalies.Furthermore,we introduce a novel hypersphere mapping technique in the latent space to distinctly separate normal and anomalous data.This mapping is the key to our model’s ability to pinpoint anomalies with greater precision.An extensive experimental setup was used to validate the efficacy of the proposed model.Using attributed social network datasets,we demonstrate that our model not only competes with but also surpasses existing state-of-the-art methods in anomaly detection.The results show the exceptional capability of our model to handle the multifaceted nature of real-world networks.
基金financially supported by the National Natural Science Foundation of China(No.41901132)the Natural Scientific Project of Guangxi Zhuang Autonomous Region(Nos.2019GXNSFAA185015,2021GXNSFBA220025)+1 种基金the Interdisciplinary Scientific Research Foundation of Guangxi University(No.2022JCC026)the Project of Key Laboratory of Early Rapid Identification,Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan Province(No.KLGDTC-2021-01)。
文摘Granite residual soil slope is often destroyed,which poses great threats to Rong County in southeastern Guangxi,China.Heavy rainfall and fissures are the major triggering and internal factors.The fissure that controls the slope stability and the associated failure mechanisms remain unclear.The purpose of this study was to identify the controlling fissures through field investigation,elucidate the effect of its position,and analyze the failure process and hydrological response of residual soil slope through artificial flume model tests.The results comprised five aspects.(1)Surface weathering and unloading fissures could affect slope stability.(2)The failure processes with different fissure positions exhibited inconsistent characteristics.(3)The volume moisture content(VMC)had the most direct response at the fissure tip.The corresponding infiltration rate was the highest.The response time of pore water pressure(PWP)was longer than that of VMC.Fluctuations in PWP were associated with VMC and changes in the soil microstructure due to local deformation.(4)Slope failure was accompanied by serious soil erosion.This could be attributed to the infiltration direction and the interaction between soil and water.(5)Fissured soil slopes experienced five similar failure processes:sheet erosion and partial failure of the slope foot,occurrence of preferential flow and enlargement of the sliding area,creep deformation and tension fissure emergence,block sliding and gully erosion,and flow-slip.
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The SEU Innovation Capability Enhancement Plan for Doctoral Students(No.CXJH_SEU 24115)Marine Economic Development Project of Guangdong Province(No.GDNRC[2022]25).
文摘The study aimed to address the issue of elevated residual stress levels in dissimilar girth welds of cast steel joints.To achieve this,the hybrid welding technology,which yields high welding speeds while simultaneously reducing residual stresses,has been introduced.This study utilizes a numerical simulation method to investigate the temperature and residual stress field in the hybrid welding of G20Mn5 casting-Q355 low-alloy steel welded pipe.A com-parison of the findings of this study with those of other welding processes revealed the technological advantages of hybrid welding.The research outcomes show that due to geometric discontinuities and material differences,the temperature field of the joint exhibits uneven distribution characteristics,and the peak temperatures on the Q355 steel side exceeds those on the G20Mn5 steel side.An evident stress gra-dient is present in the residual stress field of the joint post-welding,with peak stress located at the weld root on the Q355 steel.Compared with arc welding,the hybrid welding leads to decreased residual stresses and deformation,with high stress outside the heat-affected zone diminishing rapidly.Furthermore,it significantly improves the welding efficiency.This study elucidates the distribution and underlying causes of thermal and residual stress fields in dissimilar girth welds.This serves as a foundation for the application of hybrid welding technology in welded cast steel joints.
