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
Granite residual soil (GRS) is a type of weathering soil that can decompose upon contact with water, potentially causing geological hazards. In this study, cement, an alkaline solution, and glass fiber were used to re...Granite residual soil (GRS) is a type of weathering soil that can decompose upon contact with water, potentially causing geological hazards. In this study, cement, an alkaline solution, and glass fiber were used to reinforce GRS. The effects of cement content and SiO_(2)/Na2O ratio of the alkaline solution on the static and dynamic strengths of GRS were discussed. Microscopically, the reinforcement mechanism and coupling effect were examined using X-ray diffraction (XRD), micro-computed tomography (micro-CT), and scanning electron microscopy (SEM). The results indicated that the addition of 2% cement and an alkaline solution with an SiO_(2)/Na2O ratio of 0.5 led to the densest matrix, lowest porosity, and highest static compressive strength, which was 4994 kPa with a dynamic impact resistance of 75.4 kN after adding glass fiber. The compressive strength and dynamic impact resistance were a result of the coupling effect of cement hydration, a pozzolanic reaction of clay minerals in the GRS, and the alkali activation of clay minerals. Excessive cement addition or an excessively high SiO_(2)/Na2O ratio in the alkaline solution can have negative effects, such as the destruction of C-(A)-S-H gels by the alkaline solution and hindering the production of N-A-S-H gels. This can result in damage to the matrix of reinforced GRS, leading to a decrease in both static and dynamic strengths. This study suggests that further research is required to gain a more precise understanding of the effects of this mixture in terms of reducing our carbon footprint and optimizing its properties. The findings indicate that cement and alkaline solution are appropriate for GRS and that the reinforced GRS can be used for high-strength foundation and embankment construction. The study provides an analysis of strategies for mitigating and managing GRS slope failures, as well as enhancing roadbed performance.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
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
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
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
Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.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
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
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
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
Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation...Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.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
In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to...In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to Lie point symmetry in a properly prolonged system,based on which we get a new Bäcklund transformation for this system.New symmetry reduction solutions of the DSSH system are obtained by applying the classical Lie group approach on the prolonged system.Moreover,the DSSH system proves to be CRE integrable and new interesting interaction solutions between solitons and periodic waves are generated and analyzed.展开更多
Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canol...Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canola.Butisanstar(BUT)and clopyralid(CLO)are widely used for broadleaf weed control in these rotations.However,how residual herbicide activity influences cotton growth and development is not well understood.This study evaluated these residual effects by measuring multiple growth parameters in a greenhouse.Cotton was grown for 40 days in soil incubated for 90 days with herbicide treatments arranged in a factorial design(type:BUT,CLO,and their combination;dose:0,1/2,1,2,and 5×recommended field dose[RFD]).Results Herbicide residues reduced cotton growth in a dose-dependent manner,with greater inhibition at higher doses.The combined BUT+CLO treatment produced the strongest negative effects,followed by CLO and then BUT alone.Compared with controls,seedling emergence declined by 12%–83%,root length by 12%–87%,plant height by 10%–84%,and chlorophyll index by 12%–80%across treatments from 1/2×RFD BUT to 5×RFD BUT+CLO.Root and shoot biomass also decreased significantly.Under the 5×RFD combined treatment,shoot N,P,and K concentrations dropped by 48%,78%,and 70%,respectively,relative to the control.Conclusions Even low levels of residual BUT and CLO impair cotton growth.To mitigate these effects,it should avoid planting cotton on recently treated soils,leave sufficient intervals between herbicide application and cotton planting,and apply soil amendments to boost microbial degradation.These measures are essential for sustaining soil health and cotton productivity.展开更多
This work investigates the influence of carbon residue on the crystallization and solidification behavior of slag at different temperatures and cooling methods as it has a significant impact on the flow and discharge ...This work investigates the influence of carbon residue on the crystallization and solidification behavior of slag at different temperatures and cooling methods as it has a significant impact on the flow and discharge of slag,as well as the proper functioning of gasification equipment.The experimental approach involves the utilization of various techniques,namely ash fusion temperature(AFT)tests,X-ray fluorescence spectroscopy,X-ray diffraction(XRD),scanning electron microscopy(SEM),differential thermal analysis(DSC),and K-value semiquantitative analysis.The results obtained from ash fusion temperature(AFT)tests indicate that the coarse slag exhibits a relatively higher flow temperature compared to the decarburized coarse slag.XRD analysis reveals the presence of diffraction peaks corresponding to Fe and Fe3Si when residue carbon is present in the slag.In contrast,no such peaks are observed in the decarburized coarse slag subjected to the same temperature and cooling mode.This implying that the carbothermal reaction affects the slag's crystallization behavior,consequently influencing the flow temperature in the presence of residual carbon.SEM analysis illustrates that the spheroidization phenomenon is obvious when there is residual carbon in the coarse slag,but there is no spheroidization phenomenon in the decarburized coarse slag.This shows that the surface tension of slag is affected by the presence of residual carbon.Furthermore,DSC results confirm the crystallization transformation and mineral decomposition of the slag at high temperatures.For both carbon-containing slag and decarburized coarse slag,the content of crystals obtained under quenching condition is obviously lower than that under natural cooling condition.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
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the support provided by the National Natural Science Foundation of China(Grant Nos.52278336 and 42302032)Guangdong Basic and Applied Research Foundation(Grant Nos.2023B1515020061).
文摘Granite residual soil (GRS) is a type of weathering soil that can decompose upon contact with water, potentially causing geological hazards. In this study, cement, an alkaline solution, and glass fiber were used to reinforce GRS. The effects of cement content and SiO_(2)/Na2O ratio of the alkaline solution on the static and dynamic strengths of GRS were discussed. Microscopically, the reinforcement mechanism and coupling effect were examined using X-ray diffraction (XRD), micro-computed tomography (micro-CT), and scanning electron microscopy (SEM). The results indicated that the addition of 2% cement and an alkaline solution with an SiO_(2)/Na2O ratio of 0.5 led to the densest matrix, lowest porosity, and highest static compressive strength, which was 4994 kPa with a dynamic impact resistance of 75.4 kN after adding glass fiber. The compressive strength and dynamic impact resistance were a result of the coupling effect of cement hydration, a pozzolanic reaction of clay minerals in the GRS, and the alkali activation of clay minerals. Excessive cement addition or an excessively high SiO_(2)/Na2O ratio in the alkaline solution can have negative effects, such as the destruction of C-(A)-S-H gels by the alkaline solution and hindering the production of N-A-S-H gels. This can result in damage to the matrix of reinforced GRS, leading to a decrease in both static and dynamic strengths. This study suggests that further research is required to gain a more precise understanding of the effects of this mixture in terms of reducing our carbon footprint and optimizing its properties. The findings indicate that cement and alkaline solution are appropriate for GRS and that the reinforced GRS can be used for high-strength foundation and embankment construction. The study provides an analysis of strategies for mitigating and managing GRS slope failures, as well as enhancing roadbed performance.
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.
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 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.
基金support for this work was supported by Key Lab of Intelligent and Green Flexographic Printing under Grant ZBKT202301.
文摘Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
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.
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.
文摘Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.
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 National Natural Science Foundation of China under Grant Nos.12175148 and 11975156。
文摘In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to Lie point symmetry in a properly prolonged system,based on which we get a new Bäcklund transformation for this system.New symmetry reduction solutions of the DSSH system are obtained by applying the classical Lie group approach on the prolonged system.Moreover,the DSSH system proves to be CRE integrable and new interesting interaction solutions between solitons and periodic waves are generated and analyzed.
文摘Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canola.Butisanstar(BUT)and clopyralid(CLO)are widely used for broadleaf weed control in these rotations.However,how residual herbicide activity influences cotton growth and development is not well understood.This study evaluated these residual effects by measuring multiple growth parameters in a greenhouse.Cotton was grown for 40 days in soil incubated for 90 days with herbicide treatments arranged in a factorial design(type:BUT,CLO,and their combination;dose:0,1/2,1,2,and 5×recommended field dose[RFD]).Results Herbicide residues reduced cotton growth in a dose-dependent manner,with greater inhibition at higher doses.The combined BUT+CLO treatment produced the strongest negative effects,followed by CLO and then BUT alone.Compared with controls,seedling emergence declined by 12%–83%,root length by 12%–87%,plant height by 10%–84%,and chlorophyll index by 12%–80%across treatments from 1/2×RFD BUT to 5×RFD BUT+CLO.Root and shoot biomass also decreased significantly.Under the 5×RFD combined treatment,shoot N,P,and K concentrations dropped by 48%,78%,and 70%,respectively,relative to the control.Conclusions Even low levels of residual BUT and CLO impair cotton growth.To mitigate these effects,it should avoid planting cotton on recently treated soils,leave sufficient intervals between herbicide application and cotton planting,and apply soil amendments to boost microbial degradation.These measures are essential for sustaining soil health and cotton productivity.
基金supported by“the Fundamental Research Funds for the Central Universities”,North Minzu University(2022XYZHG07).
文摘This work investigates the influence of carbon residue on the crystallization and solidification behavior of slag at different temperatures and cooling methods as it has a significant impact on the flow and discharge of slag,as well as the proper functioning of gasification equipment.The experimental approach involves the utilization of various techniques,namely ash fusion temperature(AFT)tests,X-ray fluorescence spectroscopy,X-ray diffraction(XRD),scanning electron microscopy(SEM),differential thermal analysis(DSC),and K-value semiquantitative analysis.The results obtained from ash fusion temperature(AFT)tests indicate that the coarse slag exhibits a relatively higher flow temperature compared to the decarburized coarse slag.XRD analysis reveals the presence of diffraction peaks corresponding to Fe and Fe3Si when residue carbon is present in the slag.In contrast,no such peaks are observed in the decarburized coarse slag subjected to the same temperature and cooling mode.This implying that the carbothermal reaction affects the slag's crystallization behavior,consequently influencing the flow temperature in the presence of residual carbon.SEM analysis illustrates that the spheroidization phenomenon is obvious when there is residual carbon in the coarse slag,but there is no spheroidization phenomenon in the decarburized coarse slag.This shows that the surface tension of slag is affected by the presence of residual carbon.Furthermore,DSC results confirm the crystallization transformation and mineral decomposition of the slag at high temperatures.For both carbon-containing slag and decarburized coarse slag,the content of crystals obtained under quenching condition is obviously lower than that under natural cooling condition.
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.
