Background Virtual-reality(VR)fusion techniques have become increasingly popular in recent years,and several previous studies have applied them to laboratory education.However,without a basis for evaluating the effect...Background Virtual-reality(VR)fusion techniques have become increasingly popular in recent years,and several previous studies have applied them to laboratory education.However,without a basis for evaluating the effects of virtual-real fusion on VR in education,many developers have chosen to abandon this expensive and complex set of techniques.Methods In this study,we experimentally investigate the effects of virtual-real fusion on immersion,presence,and learning performance.Each participant was randomly assigned to one of three conditions:a PC environment(PCE)operated by mouse;a VR environment(VRE)operated by controllers;or a VR environment running virtual-real fusion(VR VRFE),operated by real hands.Results The analysis of variance(ANOVA)and t-test results for presence and self-efficacy show significant differences between the PCE*VR-VRFE condition pair.Furthermore,the results show significant differences in the intrinsic value of learning performance for pairs PCE*VR VRFE and VRE*VR-VRFE,and a marginally significant difference was found for the immersion group.Conclusions The results suggest that virtual-real fusion can offer improved immersion,presence,and self efficacy compared to traditional PC environments,as well as a better intrinsic value of learning performance compared to both PC and VR environments.The results also suggest that virtual-real fusion offers a lower sense of presence compared to traditional VR environments.展开更多
In view of the phased development in college education,military training,and new equipment combat training,this paper proposes the virtual-real fusion training model of“five-in-one and step-by-step.”The five trainin...In view of the phased development in college education,military training,and new equipment combat training,this paper proposes the virtual-real fusion training model of“five-in-one and step-by-step.”The five training modes,namely virtual panel training,immersive virtual training,physical(semi-physical)simulation training,training with equipped training equipment,and installation drill,are organically combined in the practical training of new equipment,which improves students' innovation consciousness and serviceability.展开更多
A dual-phase synergistic enhancement method was adopted to strengthen the Al-Mn-Mg-Sc-Zr alloy fabricated by laser powder bed fusion(LPBF)by leveraging the unique advantages of Er and TiB_(2).Spherical powders of 0.5w...A dual-phase synergistic enhancement method was adopted to strengthen the Al-Mn-Mg-Sc-Zr alloy fabricated by laser powder bed fusion(LPBF)by leveraging the unique advantages of Er and TiB_(2).Spherical powders of 0.5wt%Er-1wt%TiB_(2)/Al-Mn-Mg-Sc-Zr nanocomposite were prepared using vacuum homogenization technique,and the density of samples prepared through the LPBF process reached 99.8%.The strengthening and toughening mechanisms of Er-TiB_(2)were investigated.The results show that Al_(3)Er diffraction peaks are detected by X-ray diffraction analysis,and texture strength decreases according to electron backscatter diffraction results.The added Er and TiB_(2)nano-reinforcing phases act as heterogeneous nucleation sites during the LPBF forming process,hindering grain growth and effectively refining the grains.After incorporating the Er-TiB_(2)dual-phase nano-reinforcing phases,the tensile strength and elongation at break of the LPBF-deposited samples reach 550 MPa and 18.7%,which are 13.4%and 26.4%higher than those of the matrix material,respectively.展开更多
Fault diagnosis of rolling bearings is crucial for ensuring the stable operation of mechanical equipment and production safety in industrial environments.However,due to the nonlinearity and non-stationarity of collect...Fault diagnosis of rolling bearings is crucial for ensuring the stable operation of mechanical equipment and production safety in industrial environments.However,due to the nonlinearity and non-stationarity of collected vibration signals,single-modal methods struggle to capture fault features fully.This paper proposes a rolling bearing fault diagnosis method based on multi-modal information fusion.The method first employs the Hippopotamus Optimization Algorithm(HO)to optimize the number of modes in Variational Mode Decomposition(VMD)to achieve optimal modal decomposition performance.It combines Convolutional Neural Networks(CNN)and Gated Recurrent Units(GRU)to extract temporal features from one-dimensional time-series signals.Meanwhile,the Markovian Transition Field(MTF)is used to transform one-dimensional signals into two-dimensional images for spatial feature mining.Through visualization techniques,the effectiveness of generated images from different parameter combinations is compared to determine the optimal parameter configuration.A multi-modal network(GSTCN)is constructed by integrating Swin-Transformer and the Convolutional Block Attention Module(CBAM),where the attention module is utilized to enhance fault features.Finally,the fault features extracted from different modalities are deeply fused and fed into a fully connected layer to complete fault classification.Experimental results show that the GSTCN model achieves an average diagnostic accuracy of 99.5%across three datasets,significantly outperforming existing comparison methods.This demonstrates that the proposed model has high diagnostic precision and good generalization ability,providing an efficient and reliable solution for rolling bearing fault diagnosis.展开更多
BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery...BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.展开更多
BACKGROUND Salvage of the infected long stem revision total knee arthroplasty is challenging due to the presence of well-fixed ingrown or cemented stems.Reconstructive options are limited.Above knee amputation(AKA)is ...BACKGROUND Salvage of the infected long stem revision total knee arthroplasty is challenging due to the presence of well-fixed ingrown or cemented stems.Reconstructive options are limited.Above knee amputation(AKA)is often recommended.We present a surgical technique that was successfully used on four such patients to convert them to a knee fusion(KF)using a cephalomedullary nail.CASE SUMMARY Four patients with infected long stem revision knee replacements that refused AKA had a single stage removal of their infected revision total knee followed by a KF.They were all treated with a statically locked antegrade cephalomedullary fusion nail,augmented with antibiotic impregnated bone cement.All patients had successful limb salvage and were ambulatory with assistive devices at the time of last follow-up.All were infection free at an average follow-up of 25.5 months(range 16-31).CONCLUSION Single stage cephalomedullary nailing can result in a successful KF in patients with infected long stem revision total knees.展开更多
Quadruped robots which have flexibility and load-bearing capacity,are regarded as the best mobile platform for remote operation in unstructured and restricted environments.In the process of remote operation of quadrup...Quadruped robots which have flexibility and load-bearing capacity,are regarded as the best mobile platform for remote operation in unstructured and restricted environments.In the process of remote operation of quadruped robots,their status is inevitably influenced by complex environments.To monitor the robot's real-time operation status and make necessary adjustments,this paper focuses on the single-leg of a quadruped robot,proposes a single-leg virtual-real interaction system based on Digital Twin,and studies its virtual-real interaction characteristics.The virtual-reality interaction system contains single-leg physical entity,single-leg virtual model,control system,data service system and communication system,enabling interactive applications for single-leg visual state monitoring and real-time control optimization.This paper creates a high-fidelity model based on the physical entity;provides a system performance analysis method based on the system framework;analyzes virtual-real interaction delay based on communication scheme;conducts stand and jump test based on the single-leg mathematical model and analyzes the interaction characteristics under position/force control.This system provides new insights for real-time monitoring and control optimization of quadruped robots.展开更多
This is an attempt to explain mRNA-dependent non-stationary semantic values of codons (triplets) and nucleotides (letters) in codon composition during protein biosynthesis. This explanation is realized by comparing th...This is an attempt to explain mRNA-dependent non-stationary semantic values of codons (triplets) and nucleotides (letters) in codon composition during protein biosynthesis. This explanation is realized by comparing the different protein codes of various biosystem taxa, and, comparing mitochondrial code with the standard code. An initial mRNA transcriptional virtuality (Virtual-Reality) is transformed into material reality at the level of translation of virtual triplets into real (material) amino acids or into a real stop command of protein biosynthesis. The transformation of virtuality into reality occurs de facto when the linguistic sign1 functions of the codon syhoms are realized in the 3’ nucleotide (wobbling nucleotide according to F. Crick) in the process of protein biosynthesis. This corresponds to the theoretical works of the authors of this article. Despite the illusory appearance of semantic arbitrariness during the operation of ribosomes in the mode of codon semantic non-stationarity, this phenomenon probably provides biosystems with an unusually high level of adaptability to changes in the external environment as well as to internal (mental) dynamics of neuron’s genome in the cerebral cortex. The genome’s non-stationarity properties at the nucleotide, codon, gene and mental levels have fractal structure and corresponding dimensions. The highest form of such fractality (with maximum dimension) is probably realized in the genomic continuum of neurons in the human cerebral cortex through this semantic Virtual-to-Real (VR) codon transcoding with the biosynthesis of short-living semantic proteins, as the equivalents of material thinking-consciousness. In fact, this is the language of the brain’s genome, that is, our own language. In this case, the same thing happens in natural, primarily mental (non-verbal) languages. Their materialization is recorded in vocables (sounding words) and in writing. Such writing is the amino acid sequence in the semantic proteins of the human cerebral cortex. Rapidly decaying, such proteins can leave a long-lasting “so-called” Schrödinger wave holographic memory in the cerebral cortex. The presented below study is purely theoretical and based on a logical approach. The topic of the study is very complex and is subject to further development.展开更多
To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0....To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0.27%to 0.22%,enabling the elements Mo and Ti to diffuse fully and to distribute more uniformly,and to forming a substantial number of low-angle grain boundaries.The tensile strength soars from 286±32 MPa to 598±22 MPa,while the elongation increases from 0.08%±0.02%to 0.18%±0.02%,without notable alterations in grain morphology during the tensile deformation.HIP treatment eliminates the molten pool boundaries,which are the primary source for premature failure in LPBFed Mo alloys.Consequently,HIP treatment emerges as a novel and effective approach for strengthening the mechanical properties of LPBFed Mo alloys,offering a fresh perspective on producing high-performance Mo-based alloys.展开更多
Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.There...Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.展开更多
In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Ela...In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.展开更多
In this editorial,the authors of this paper comment on the article by Bokov et al published in the recent issue of World Journal of Orthopedics.We reviewed a general overview of oblique lumbar interbody fusions(OLIF)a...In this editorial,the authors of this paper comment on the article by Bokov et al published in the recent issue of World Journal of Orthopedics.We reviewed a general overview of oblique lumbar interbody fusions(OLIF)and lateral lumbar interbody fusions(LLIF),their indications and complications as an increasingly popular minimally invasive technique to address several lumbar pathologies.This editorial thoroughly discusses and reviews the literature regarding factors affecting outcomes of indirect decompression utilized through OLIF and LLIF procedures.Several parameters play a critical role in patient outcomes including restoration of disc height,foraminal height,central canal squared,and foraminal area.The indirect decompression allows for unbuckling of the ligamentum flavum which can significantly decompress the neural elements as well as aid in reduction of spondylolisthesis.However,the authors further highlight the limitations of indirect decompression and factors that may predict unsuccessful outcomes including bony foraminal stenosis,severe central canal stenosis,and osteoporosis.As a result,failure of indirect decompression can lead to persistent pain,radiculopathy and unsatisfied patients.Spinal surgeons may be left to reimage patients and consider additional procedures with direct decompression.展开更多
Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit fr...Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit frustrating magnetostriction coefficients when presented in bulk dimensions.It is well-established that the magnetostrictive performance of Fe-Ga alloys is intimately linked to their phase and crystal structures.In this study,various concentrations of boron(B)were doped into Fe_(81)Ga_(19) alloys via the laser-beam powder bed fusion(LPBF)technique to tailor the crystal and phase structures,thereby improving the magnetostrictive performance.The results revealed the capacity for quick solidification of the LPBF process in expediting the solid solution of B element,which increased both lattice distortion and dislocations within the Fe-Ga matrix.These factors contributed to an elevation in the density of the modified-D0_(3) phase structure.Moreover,the prepared Fe-Ga-B alloys also exhibited a(001)preferred grain orientation caused by the high thermal gradients during the LPBF process.As a result,a maximum magnetostriction coefficient of 105 ppm was achieved in the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy.In alternating magnetic fields,all the LPBF-prepared alloys showed good dynamic magnetostriction response without visible hysteresis,while the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy presented a notable enhancement of~30%in magnetostriction coefficient when compared with the Fe_(81)Ga_(19) alloy.Moreover.the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy exhibited favorable biocompatibility and osteogenesis,as confirmed by increased alkaline phosphatase(ALP)activity and the formation of mineralized nodules.These findings suggest that the B-doped Fe-Ga alloys combined with the LPBF technique hold promise for the development of bulk magnetostrictive alloys that are applicable for bone repair applications.展开更多
The accurate prediction of drug absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties represents a crucial step in early drug development for reducing failure risk.Current deep learning approaches...The accurate prediction of drug absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties represents a crucial step in early drug development for reducing failure risk.Current deep learning approaches face challenges with data sparsity and information loss due to single-molecule representation limitations and isolated predictive tasks.This research proposes molecular properties prediction with parallel-view and collaborative learning(MolP-PC),a multi-view fusion and multi-task deep learning framework that integrates 1D molecular fingerprints(MFs),2D molecular graphs,and 3D geometric representations,incorporating an attention-gated fusion mechanism and multi-task adaptive learning strategy for precise ADMET property predictions.Experimental results demonstrate that MolP-PC achieves optimal performance in 27 of 54 tasks,with its multi-task learning(MTL)mechanism significantly enhancing predictive performance on small-scale datasets and surpassing single-task models in 41 of 54 tasks.Additional ablation studies and interpretability analyses confirm the significance of multi-view fusion in capturing multi-dimensional molecular information and enhancing model generalization.A case study examining the anticancer compound Oroxylin A demonstrates MolP-PC’s effective generalization in predicting key pharmacokinetic parameters such as half-life(T0.5)and clearance(CL),indicating its practical utility in drug modeling.However,the model exhibits a tendency to underestimate volume of distribution(VD),indicating potential for improvement in analyzing compounds with high tissue distribution.This study presents an efficient and interpretable approach for ADMET property prediction,establishing a novel framework for molecular optimization and risk assessment in drug development.展开更多
The features of additive manufacturing(AM)have made commercially pure titanium(CP-Ti)an attractive candidate material for biomedical implants.However,achieving high strength and ductility is challenging because of the...The features of additive manufacturing(AM)have made commercially pure titanium(CP-Ti)an attractive candidate material for biomedical implants.However,achieving high strength and ductility is challenging because of the columnar structures and fine martensite formation.This study investigated the effect of carbon nanotubes(CNTs)addition on the microstructure and mechanical properties of grade 1 CP-Ti(Gr-1)during the laser powder bed fusion(L-PBF)process.A minute amount of 0.2%mass fraction(wt%)CNTs addition resulted in a high yield strength of approximately 700 MPa and exceptional ductility of 25.7%.Therein,a portion of the CNTs dissolved in the matrix as solute atoms,contributing to solution strengthening,while others were transformed into Ti C_(x)through an in situ reaction with the Ti matrix.Furthermore,the addition of CNTs resulted in the formation of a larger fraction of equiaxed grains and increased the activity of basal and prismatic slip systems.Hence,Gr-1 with CNTs exhibited significantly increased ductility while maintaining a high strength comparable to that of Gr-1 without CNTs.The insights gained from this study provide a novel approach for designing strong and ductile Ti alloys for AM.展开更多
This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysi...This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.展开更多
基金the National Key Research and Development Program of China(2018YFB1004902)the National Natural Science Foundation of China(61772329,61373085)。
文摘Background Virtual-reality(VR)fusion techniques have become increasingly popular in recent years,and several previous studies have applied them to laboratory education.However,without a basis for evaluating the effects of virtual-real fusion on VR in education,many developers have chosen to abandon this expensive and complex set of techniques.Methods In this study,we experimentally investigate the effects of virtual-real fusion on immersion,presence,and learning performance.Each participant was randomly assigned to one of three conditions:a PC environment(PCE)operated by mouse;a VR environment(VRE)operated by controllers;or a VR environment running virtual-real fusion(VR VRFE),operated by real hands.Results The analysis of variance(ANOVA)and t-test results for presence and self-efficacy show significant differences between the PCE*VR-VRFE condition pair.Furthermore,the results show significant differences in the intrinsic value of learning performance for pairs PCE*VR VRFE and VRE*VR-VRFE,and a marginally significant difference was found for the immersion group.Conclusions The results suggest that virtual-real fusion can offer improved immersion,presence,and self efficacy compared to traditional PC environments,as well as a better intrinsic value of learning performance compared to both PC and VR environments.The results also suggest that virtual-real fusion offers a lower sense of presence compared to traditional VR environments.
基金The 2019 Ministry of Education Industry-University Cooperation Collaborative Education Project"Research on the Construction of Economics and Management Professional Data Analysis Laboratory"(Grant Number:201902077020)。
文摘In view of the phased development in college education,military training,and new equipment combat training,this paper proposes the virtual-real fusion training model of“five-in-one and step-by-step.”The five training modes,namely virtual panel training,immersive virtual training,physical(semi-physical)simulation training,training with equipped training equipment,and installation drill,are organically combined in the practical training of new equipment,which improves students' innovation consciousness and serviceability.
基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Construction Project(2022KXJ-071)2022 Qin Chuangyuan Achievement Transformation Incubation Capacity Improvement Project(2022JH-ZHFHTS-0012)+8 种基金Shaanxi Province Key Research and Development Plan-“Two Chains”Integration Key Project-Qin Chuangyuan General Window Industrial Cluster Project(2023QCY-LL-02)Xixian New Area Science and Technology Plan(2022-YXYJ-003,2022-XXCY-010)2024 Scientific Research Project of Shaanxi National Defense Industry Vocational and Technical College(Gfy24-07)Shaanxi Vocational and Technical Education Association 2024 Vocational Education Teaching Reform Research Topic(2024SZX354)National Natural Science Foundation of China(U24A20115)2024 Shaanxi Provincial Education Department Service Local Special Scientific Research Program Project-Industrialization Cultivation Project(24JC005,24JC063)Shaanxi Province“14th Five-Year Plan”Education Science Plan,2024 Project(SGH24Y3181)National Key Research and Development Program of China(2023YFB4606400)Longmen Laboratory Frontier Exploration Topics Project(LMQYTSKT003)。
文摘A dual-phase synergistic enhancement method was adopted to strengthen the Al-Mn-Mg-Sc-Zr alloy fabricated by laser powder bed fusion(LPBF)by leveraging the unique advantages of Er and TiB_(2).Spherical powders of 0.5wt%Er-1wt%TiB_(2)/Al-Mn-Mg-Sc-Zr nanocomposite were prepared using vacuum homogenization technique,and the density of samples prepared through the LPBF process reached 99.8%.The strengthening and toughening mechanisms of Er-TiB_(2)were investigated.The results show that Al_(3)Er diffraction peaks are detected by X-ray diffraction analysis,and texture strength decreases according to electron backscatter diffraction results.The added Er and TiB_(2)nano-reinforcing phases act as heterogeneous nucleation sites during the LPBF forming process,hindering grain growth and effectively refining the grains.After incorporating the Er-TiB_(2)dual-phase nano-reinforcing phases,the tensile strength and elongation at break of the LPBF-deposited samples reach 550 MPa and 18.7%,which are 13.4%and 26.4%higher than those of the matrix material,respectively.
基金funded by the Jilin Provincial Department of Science and Technology,grant number 20230101208JC.
文摘Fault diagnosis of rolling bearings is crucial for ensuring the stable operation of mechanical equipment and production safety in industrial environments.However,due to the nonlinearity and non-stationarity of collected vibration signals,single-modal methods struggle to capture fault features fully.This paper proposes a rolling bearing fault diagnosis method based on multi-modal information fusion.The method first employs the Hippopotamus Optimization Algorithm(HO)to optimize the number of modes in Variational Mode Decomposition(VMD)to achieve optimal modal decomposition performance.It combines Convolutional Neural Networks(CNN)and Gated Recurrent Units(GRU)to extract temporal features from one-dimensional time-series signals.Meanwhile,the Markovian Transition Field(MTF)is used to transform one-dimensional signals into two-dimensional images for spatial feature mining.Through visualization techniques,the effectiveness of generated images from different parameter combinations is compared to determine the optimal parameter configuration.A multi-modal network(GSTCN)is constructed by integrating Swin-Transformer and the Convolutional Block Attention Module(CBAM),where the attention module is utilized to enhance fault features.Finally,the fault features extracted from different modalities are deeply fused and fed into a fully connected layer to complete fault classification.Experimental results show that the GSTCN model achieves an average diagnostic accuracy of 99.5%across three datasets,significantly outperforming existing comparison methods.This demonstrates that the proposed model has high diagnostic precision and good generalization ability,providing an efficient and reliable solution for rolling bearing fault diagnosis.
基金Supported by the Scientific Research Projects of the Health System in Pingshan District,No.2023122.
文摘BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.
文摘BACKGROUND Salvage of the infected long stem revision total knee arthroplasty is challenging due to the presence of well-fixed ingrown or cemented stems.Reconstructive options are limited.Above knee amputation(AKA)is often recommended.We present a surgical technique that was successfully used on four such patients to convert them to a knee fusion(KF)using a cephalomedullary nail.CASE SUMMARY Four patients with infected long stem revision knee replacements that refused AKA had a single stage removal of their infected revision total knee followed by a KF.They were all treated with a statically locked antegrade cephalomedullary fusion nail,augmented with antibiotic impregnated bone cement.All patients had successful limb salvage and were ambulatory with assistive devices at the time of last follow-up.All were infection free at an average follow-up of 25.5 months(range 16-31).CONCLUSION Single stage cephalomedullary nailing can result in a successful KF in patients with infected long stem revision total knees.
文摘Quadruped robots which have flexibility and load-bearing capacity,are regarded as the best mobile platform for remote operation in unstructured and restricted environments.In the process of remote operation of quadruped robots,their status is inevitably influenced by complex environments.To monitor the robot's real-time operation status and make necessary adjustments,this paper focuses on the single-leg of a quadruped robot,proposes a single-leg virtual-real interaction system based on Digital Twin,and studies its virtual-real interaction characteristics.The virtual-reality interaction system contains single-leg physical entity,single-leg virtual model,control system,data service system and communication system,enabling interactive applications for single-leg visual state monitoring and real-time control optimization.This paper creates a high-fidelity model based on the physical entity;provides a system performance analysis method based on the system framework;analyzes virtual-real interaction delay based on communication scheme;conducts stand and jump test based on the single-leg mathematical model and analyzes the interaction characteristics under position/force control.This system provides new insights for real-time monitoring and control optimization of quadruped robots.
文摘This is an attempt to explain mRNA-dependent non-stationary semantic values of codons (triplets) and nucleotides (letters) in codon composition during protein biosynthesis. This explanation is realized by comparing the different protein codes of various biosystem taxa, and, comparing mitochondrial code with the standard code. An initial mRNA transcriptional virtuality (Virtual-Reality) is transformed into material reality at the level of translation of virtual triplets into real (material) amino acids or into a real stop command of protein biosynthesis. The transformation of virtuality into reality occurs de facto when the linguistic sign1 functions of the codon syhoms are realized in the 3’ nucleotide (wobbling nucleotide according to F. Crick) in the process of protein biosynthesis. This corresponds to the theoretical works of the authors of this article. Despite the illusory appearance of semantic arbitrariness during the operation of ribosomes in the mode of codon semantic non-stationarity, this phenomenon probably provides biosystems with an unusually high level of adaptability to changes in the external environment as well as to internal (mental) dynamics of neuron’s genome in the cerebral cortex. The genome’s non-stationarity properties at the nucleotide, codon, gene and mental levels have fractal structure and corresponding dimensions. The highest form of such fractality (with maximum dimension) is probably realized in the genomic continuum of neurons in the human cerebral cortex through this semantic Virtual-to-Real (VR) codon transcoding with the biosynthesis of short-living semantic proteins, as the equivalents of material thinking-consciousness. In fact, this is the language of the brain’s genome, that is, our own language. In this case, the same thing happens in natural, primarily mental (non-verbal) languages. Their materialization is recorded in vocables (sounding words) and in writing. Such writing is the amino acid sequence in the semantic proteins of the human cerebral cortex. Rapidly decaying, such proteins can leave a long-lasting “so-called” Schrödinger wave holographic memory in the cerebral cortex. The presented below study is purely theoretical and based on a logical approach. The topic of the study is very complex and is subject to further development.
基金National Natural Science Foundation of China(52105385)Stable Support Plan Program of Shenzhen Natural Science Fund(20220810132537001)+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010781)Joint Fund of Henan Province Science and Technology R&D Program(225200810002)Fundamental Research Funds of Henan Academy of Sciences(240621041)。
文摘To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0.27%to 0.22%,enabling the elements Mo and Ti to diffuse fully and to distribute more uniformly,and to forming a substantial number of low-angle grain boundaries.The tensile strength soars from 286±32 MPa to 598±22 MPa,while the elongation increases from 0.08%±0.02%to 0.18%±0.02%,without notable alterations in grain morphology during the tensile deformation.HIP treatment eliminates the molten pool boundaries,which are the primary source for premature failure in LPBFed Mo alloys.Consequently,HIP treatment emerges as a novel and effective approach for strengthening the mechanical properties of LPBFed Mo alloys,offering a fresh perspective on producing high-performance Mo-based alloys.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3004104)the National Natural Science Foundation of China(Grant No.U2342204)+4 种基金the Innovation and Development Program of the China Meteorological Administration(Grant No.CXFZ2024J001)the Open Research Project of the Key Open Laboratory of Hydrology and Meteorology of the China Meteorological Administration(Grant No.23SWQXZ010)the Science and Technology Plan Project of Zhejiang Province(Grant No.2022C03150)the Open Research Fund Project of Anyang National Climate Observatory(Grant No.AYNCOF202401)the Open Bidding for Selecting the Best Candidates Program(Grant No.CMAJBGS202318)。
文摘Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.
文摘In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.
文摘In this editorial,the authors of this paper comment on the article by Bokov et al published in the recent issue of World Journal of Orthopedics.We reviewed a general overview of oblique lumbar interbody fusions(OLIF)and lateral lumbar interbody fusions(LLIF),their indications and complications as an increasingly popular minimally invasive technique to address several lumbar pathologies.This editorial thoroughly discusses and reviews the literature regarding factors affecting outcomes of indirect decompression utilized through OLIF and LLIF procedures.Several parameters play a critical role in patient outcomes including restoration of disc height,foraminal height,central canal squared,and foraminal area.The indirect decompression allows for unbuckling of the ligamentum flavum which can significantly decompress the neural elements as well as aid in reduction of spondylolisthesis.However,the authors further highlight the limitations of indirect decompression and factors that may predict unsuccessful outcomes including bony foraminal stenosis,severe central canal stenosis,and osteoporosis.As a result,failure of indirect decompression can lead to persistent pain,radiculopathy and unsatisfied patients.Spinal surgeons may be left to reimage patients and consider additional procedures with direct decompression.
基金supported by the National Natural Science Foundation of China(Nos.52275395,51935014,and 82072084)the Science and Technology Innovation Program of Hunan Province(No.2023RC3046)+4 种基金the Young Elite Scientists Sponsorship Program byCAST(No.2020QNRC002)the NationalKeyResearchand Development Program of China(No.2023YFB4605800)the Central South University Innovation-Driven Research Programme(No.2023CXQD023)the Jiangxi Provincial Natural Science Foundation of China(No.20224ACB204013)the Project of State Key Laboratory of Precision Manufacturing for Extreme Service Performance,Central South University.
文摘Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit frustrating magnetostriction coefficients when presented in bulk dimensions.It is well-established that the magnetostrictive performance of Fe-Ga alloys is intimately linked to their phase and crystal structures.In this study,various concentrations of boron(B)were doped into Fe_(81)Ga_(19) alloys via the laser-beam powder bed fusion(LPBF)technique to tailor the crystal and phase structures,thereby improving the magnetostrictive performance.The results revealed the capacity for quick solidification of the LPBF process in expediting the solid solution of B element,which increased both lattice distortion and dislocations within the Fe-Ga matrix.These factors contributed to an elevation in the density of the modified-D0_(3) phase structure.Moreover,the prepared Fe-Ga-B alloys also exhibited a(001)preferred grain orientation caused by the high thermal gradients during the LPBF process.As a result,a maximum magnetostriction coefficient of 105 ppm was achieved in the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy.In alternating magnetic fields,all the LPBF-prepared alloys showed good dynamic magnetostriction response without visible hysteresis,while the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy presented a notable enhancement of~30%in magnetostriction coefficient when compared with the Fe_(81)Ga_(19) alloy.Moreover.the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy exhibited favorable biocompatibility and osteogenesis,as confirmed by increased alkaline phosphatase(ALP)activity and the formation of mineralized nodules.These findings suggest that the B-doped Fe-Ga alloys combined with the LPBF technique hold promise for the development of bulk magnetostrictive alloys that are applicable for bone repair applications.
基金supported by the research on key technologies for monitoring and identifying drug abuse of anesthetic drugs and psychotropic drugs,and intervention for addiction(No.2023YFC3304200)the program of a study on the diagnosis of addiction to synthetic cannabinoids and methods of assessing the risk of abuse(No.2022YFC3300905)+1 种基金the program of Ab initio design and generation of AI models for small molecule ligands based on target structures(No.2022PE0AC03)ZHIJIANG LAB.
文摘The accurate prediction of drug absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties represents a crucial step in early drug development for reducing failure risk.Current deep learning approaches face challenges with data sparsity and information loss due to single-molecule representation limitations and isolated predictive tasks.This research proposes molecular properties prediction with parallel-view and collaborative learning(MolP-PC),a multi-view fusion and multi-task deep learning framework that integrates 1D molecular fingerprints(MFs),2D molecular graphs,and 3D geometric representations,incorporating an attention-gated fusion mechanism and multi-task adaptive learning strategy for precise ADMET property predictions.Experimental results demonstrate that MolP-PC achieves optimal performance in 27 of 54 tasks,with its multi-task learning(MTL)mechanism significantly enhancing predictive performance on small-scale datasets and surpassing single-task models in 41 of 54 tasks.Additional ablation studies and interpretability analyses confirm the significance of multi-view fusion in capturing multi-dimensional molecular information and enhancing model generalization.A case study examining the anticancer compound Oroxylin A demonstrates MolP-PC’s effective generalization in predicting key pharmacokinetic parameters such as half-life(T0.5)and clearance(CL),indicating its practical utility in drug modeling.However,the model exhibits a tendency to underestimate volume of distribution(VD),indicating potential for improvement in analyzing compounds with high tissue distribution.This study presents an efficient and interpretable approach for ADMET property prediction,establishing a novel framework for molecular optimization and risk assessment in drug development.
基金financially supported by the National Key Research and Development Project of the Ministry of Science and Technology of China(No.2022YFB4601000)the Fundamental Research Funds for the Central Universities(No.2042023kf0103)the Ministry of Trade,Industry and Energy,Korea(No.20013095)。
文摘The features of additive manufacturing(AM)have made commercially pure titanium(CP-Ti)an attractive candidate material for biomedical implants.However,achieving high strength and ductility is challenging because of the columnar structures and fine martensite formation.This study investigated the effect of carbon nanotubes(CNTs)addition on the microstructure and mechanical properties of grade 1 CP-Ti(Gr-1)during the laser powder bed fusion(L-PBF)process.A minute amount of 0.2%mass fraction(wt%)CNTs addition resulted in a high yield strength of approximately 700 MPa and exceptional ductility of 25.7%.Therein,a portion of the CNTs dissolved in the matrix as solute atoms,contributing to solution strengthening,while others were transformed into Ti C_(x)through an in situ reaction with the Ti matrix.Furthermore,the addition of CNTs resulted in the formation of a larger fraction of equiaxed grains and increased the activity of basal and prismatic slip systems.Hence,Gr-1 with CNTs exhibited significantly increased ductility while maintaining a high strength comparable to that of Gr-1 without CNTs.The insights gained from this study provide a novel approach for designing strong and ductile Ti alloys for AM.
基金Chongqing Engineering University Undergraduate Innovation and Entrepreneurship Training Program Project:Wireless Fire Automatic Alarm System(Project No.:CXCY2024017)Chongqing Municipal Education Commission Science and Technology Research Project:Development and Research of Chongqing Wireless Fire Automatic Alarm System(Project No.:KJQN202401906)。
文摘This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.
