Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer ...Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.展开更多
软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一...软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。展开更多
Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some sho...Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some shortcomings because of the low permeability and tightness of shale,complex gas flow behavior of multi-scale gas transport regions and multiple gas transport mechanism superpositions,and complex and variable production regimes of shale gas wells.Recent research has demonstrated the existence of a multi-stage isotope fractionation phenomenon during shale gas production,with the fractionation characteristics of each stage associated with the pore structure,gas in place(GIP),adsorption/desorption,and gas production process.This study presents a new approach for estimating shale gas well production and evaluating the adsorbed/free gas ratio throughout production using isotope fractionation techniques.A reservoir-scale carbon isotope fractionation(CIF)model applicable to the production process of shale gas wells was developed for the first time in this research.In contrast to the traditional model,this model improves production prediction accuracy by simultaneously fitting the gas production rate and δ^(13)C_(1) data and provides a new evaluation method of the adsorbed/free gas ratio during shale gas production.The results indicate that the diffusion and adsorption/desorption properties of rock,bottom-hole flowing pressure(BHP)of gas well,and multi-scale gas transport regions of the reservoir all affect isotope fractionation,with the diffusion and adsorption/desorption parameters of rock having the greatest effect on isotope fractionation being D∗/D,PL,VL,α,and others in that order.We effectively tested the universality of the four-stage isotope fractionation feature and revealed a unique isotope fractionation mechanism caused by the superimposed coupling of multi-scale gas transport regions during shale gas well production.Finally,we applied the established CIF model to a shale gas well in the Sichuan Basin,China,and calculated the estimated ultimate recovery(EUR)of the well to be 3.33×10^(8) m^(3);the adsorbed gas ratio during shale gas production was 1.65%,10.03%,and 23.44%in the first,fifth,and tenth years,respectively.The findings are significant for understanding the isotope fractionation mechanism during natural gas transport in complex systems and for formulating and optimizing unconventional natural gas development strategies.展开更多
BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential t...BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential to mitigate these adverse effects and enhance overall health outcomes in this population.AIM To evaluate the effects of exercise-cognitive dual-task training on frailty,cognitive function,psychological status,and quality of life in elderly patients with cognitive frailty and depression.METHODS A retrospective study was conducted on 130 patients with cognitive frailty and depression admitted between December 2021 and December 2023.Patients were divided into a control group receiving routine intervention and an observation group undergoing exercise-cognitive dual-task training in addition to routine care.Frailty,cognitive function,balance and gait,psychological status,and quality of life were assessed before and after the intervention.RESULTS After the intervention,the frailty score of the observation group was(5.32±0.69),lower than that of the control group(5.71±0.55).The Montreal cognitive assessment basic scale score in the observation group was(24.06±0.99),higher than the control group(23.43±1.40).The performance oriented mobility assessment score in the observation group was(21.81±1.24),higher than the control group(21.15±1.26).The self-efficacy in the observation group was(28.27±2.66),higher than the control group(30.05±2.66).The anxiety score in the hospital anxiety and depression scale(HADS)for the observation group was(5.86±0.68),lower than the control group(6.21±0.64).The depression score in the HADS for the observation group was(5.67±0.75),lower than the control group(6.27±0.92).Additionally,the scores for each dimension of the 36-item short form survey in the observation group were higher than those in the control group,with statistically significant differences(P<0.05).CONCLUSION Exercise-cognitive dual-task training is beneficial for improving frailty,enhancing cognitive function,and improving psychological status and quality of life in elderly patients with cognitive frailty and depression.展开更多
In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accurac...In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and...A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.展开更多
Exercise is a therapeutic approach in cancer treatment,providing several benefits.Moreover,exercise is associated with a reduced risk for developing a range of cancers and for their recurrence,as well as with improvin...Exercise is a therapeutic approach in cancer treatment,providing several benefits.Moreover,exercise is associated with a reduced risk for developing a range of cancers and for their recurrence,as well as with improving survival,even though the underlying mechanisms remain unclear.Preclinical and clinical evidence shows that the acute effects of a single exercise session can suppress the growth of various cancer cell lines in vitro.This suppression is potentially due to altered concentrations of hormones(e.g.,insulin)and cytokines(e.g.,tumor necrosis factor alpha and interleukin 6)after exercise.These factors,known to be involved in tumorigenesis,may explain why exercise is associated with reduced cancer incidence,recurrence,and mortality.However,the effects of short-(<8 weeks)and long-term(≥8 weeks)exercise programs on cancer cells have been reported with mixed results.Although more research is needed,it appears that interventions incorporating both exercise and diet seem to have greater inhibitory effects on cancer cell growth in both apparently healthy subjects as well as in cancer patients.Although speculative,these suppressive effects on cancer cells may be driven by changes in body weight and composition as well as by a reduction in low-grade inflammation often associated with sedentary behavior,low muscle mass,and excess fat mass in cancer patients.Taken together,such interventions could alter the systemic levels of suppressive circulating factors,leading to a less favorable environment for tumorigenesis.While regular exercise and a healthy diet may establish a more cancer-suppressive environment,each acute bout of exercise provides a further“dose”of anticancer medicine.Therefore,integrating regular exercise could potentially play a significant role in cancer management,highlighting the need for future investigations in this promising area of research.展开更多
Standardized residency training programs primarily focus on developing clinical diagnostic and treatment skills,often allocating limited time to research activities.However,enhancing research skills is of paramount im...Standardized residency training programs primarily focus on developing clinical diagnostic and treatment skills,often allocating limited time to research activities.However,enhancing research skills is of paramount importance for residents,as it fosters critical thinking,problem-solving abilities,and a deeper understanding of applying scientific principles to clinical practice.This paper explores the necessity and significance of integrating research training into residency programs,emphasizing its role in cultivating well-rounded physicians capable of advancing medical knowledge.This study proposes a competency-based research training model that encompasses research literacy,study design,biostatistics,and scientific writing.Additionally,online asynchronous training modules,robust mentorship,and balanced time management strategies are recommended to enhance residents’research engagement without compromising clinical training.By implementing these measures,residency programs can improve residents’research capabilities,contributing to both individual professional growth and the broader advancement of medical science.展开更多
Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhanc...Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhancement(endurance and sprints),and(b)the influence of participant characteristics and intervention protocols on these effects.Methods Searches were conducted in PubMed,Web of Science(Core Collection),Cochrane Library(Embase,ClinicalTrials.gov,and International Clinical Trials Registry Platform),and Chinese National Knowledge Infrastructure on April 2,with updates on October 17,2024.Pooled effects for each outcome were summarized using Hedge's g(g)through meta-analysis-based random effects models,and subgroup and regression analyses were used to explore moderators.Results A total of 24 studies with 621 participants were included.IT combined with BFR(IT+BFR)significantly improved maximal oxygen uptake(VO2_(max))(g=0.63,I^(2)=63%),mean power during the Wingate 30-s test(g=0.70,I^(2)=47%),muscle strength(g=0.88,I^(2)=64%),muscle endurance(g=0.43,I^(2)=0%),time to fatigue(g=1.26,I^(2)=86%),and maximal aerobic speed(g=0.74,I^(2)=0%)compared to IT alone.Subgroup analysis indicated that participant characteristics including training status,IT intensity,and IT modes significantly moderated VO2_(max)(subgroup differences:p<0.05).Specifically,IT+BFR showed significantly superior improvements in VO2_(max)compared to IT alone in trained individuals(g=0.76)at supra-maximal intensity(g=1.29)and moderate intensity(g=1.08)as well as in walking(g=1.64)and running(g=0.63)modes.Meta-regression analysis showed cuff width(β=0.14)was significantly associated with VO2_(max)change,identifying 8.23 cm as the minimum threshold required for significant improvement.Subgroup analyses regarding muscle strength did not reveal any significant moderators.Conclusion IT+BFR enhances physiological adaptations and optimizes aspects of endurance performance,with moderators including training status,IT protocol(intensity,mode,and type),and cuff width.This intervention addresses various IT-related challenges and provides tailored protocols and benefits for diverse populations.展开更多
Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a co...Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a continuous challenge university managers face.To explore a method of preventing psychological crises among college students,we measured 38661 students by using SCL-90(symptom check list-90)and screened out 5790 students with positive results.Then,we measured 33188 students by using PHQ-9(patient health questionnaire-9)and screened out 603 students with suicidal ideation or behavior;we interviewed 392 students by using GAQ(growth adversity questionnaire).The number of students who had positive results at both phases is 155.As a result,we obtained a data set(N=76)by integrating the students who tested positive on the PHQ-9(i.e.total score≥20)with those who completed the PHQ-9 and GAQ.In addition,we obtained a data set(N=50)by excluding the cases in which the GAQ score is 0.With regard to QCA(qualitative comparative analysis)results,the data set(N=76)exhibits 5 constellations of solutions with a coverage rate greater than 0.7,and the first eight indicators of the PHQ-9 constitute the explanatory variables in the combined solutions.About the data set(N=50),the combined solutions are extremely complicated and the explanatory variables encompass indicators from both the PHQ-9 and GAQ.All these mean that the multi-scale could more comprehensively reflect mental health states of college students,thus enhance the accuracy and effectiveness of the corresponding hierarchical intervention,and finally provide support for preventing psychological crises in universities.展开更多
This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessmen...This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessment Form has been assessed as severe articulation disorder.The patient has significantly improved his speech function and quality of life after systematic head control training,respiratory function training,articulation motor training,and articulation training.In the course of treatment,emphasis was placed on head postural control training and respiratory function training,and emphasis was placed on the strength and coordination training of articulatory organs,and the results were remarkable.After the patient was discharged from the hospital,the follow-up of basic daily life communication was not limited.展开更多
Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This...Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.展开更多
Background Schizophrenia is characterised by pervasive cognitive deficits that significantly impair daily functioning and quality of life.Pharmacological treatments have limited efficacy in addressing these deficits,h...Background Schizophrenia is characterised by pervasive cognitive deficits that significantly impair daily functioning and quality of life.Pharmacological treatments have limited efficacy in addressing these deficits,highlighting the need for adjunctive interventions like computerised cognitive training(CCT).Aims This study aimed to evaluate the effects of a 30-session CCT programme on mental well-being and cognitive performance in individuals with schizophrenia.Additionally,it assessed the usability and acceptability of CCT in this population.Methods A double-blind,randomised clinical trial was conducted with 54 participants assigned to intervention and control groups.Cognitive and mental health outcomes were assessed using validated tools such as the Depression Anxiety Stress Scale 21,the Warwick-Edinburgh Mental Wellbeing Scale and the Cambridge Neuropsychological Test Automated Battery.Usability was measured with the System Usability Scale(SUS).Assessments were conducted at baseline,post-intervention and 3 months post-follow-up.Results The CCT intervention significantly improved mental well-being,reduced stress and enhanced working memory(paired associate learning,spatial working memory and spatial span)compared with controls.However,no significant effects were observed for anxiety,depression or executive function.Usability scores were high(SUS=83.51),and compliance rates were strong(92.7%),indicating favourable participant engagement.Conclusion CCT demonstrated potential as an adjunctive treatment for schizophrenia,with significant improvements in targeted cognitive and mental health domains.The high usability and compliance rates support its feasibility for broader implementation.Further research is needed to optimise protocols and explore long-term benefits.CCT offers a promising approach to addressing mental health and cognitive challenges in schizophrenia,particularly for stress and working memory.Its usability and acceptability suggest it could be seamlessly integrated into clinical practice.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells an...Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells and the significant variations in cell size.Pathologists often refer to surrounding cells to identify abnormalities.To emulate this slide examination behavior,this study proposes a Multi-Scale Feature Fusion Network(MSFF-Net)for detecting cervical abnormal cells.MSFF-Net employs a Cross-Scale Pooling Model(CSPM)to effectively capture diverse features and contextual information,ranging from local details to the overall structure.Additionally,a Multi-Scale Fusion Attention(MSFA)module is introduced to mitigate the impact of cell size variations by adaptively fusing local and global information at different scales.To handle the complex environment of cervical cell images,such as cell adhesion and overlapping,the Inner-CIoU loss function is utilized to more precisely measure the overlap between bounding boxes,thereby improving detection accuracy in such scenarios.Experimental results on the Comparison detector dataset demonstrate that MSFF-Net achieves a mean average precision(mAP)of 63.2%,outperforming state-of-the-art methods while maintaining a relatively small number of parameters(26.8 M).This study highlights the effectiveness of multi-scale feature fusion in enhancing the detection of cervical abnormal cells,contributing to more accurate and efficient cervical cancer screening.展开更多
Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distin...Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distinguishing the MA contributions of different scale factors and tuning the optimal combined effects remains a formidable challenge. This study employs a synergistic approach combining template protection etching and vacuum annealing to construct a controlled system of micrometer-sized cavities and amorphous carbon matrices in metal-organic framework (MOF) derivatives. The results demonstrate that the spatial effects introduced by the hollow structure enhance dielectric loss but significantly weaken impedance matching. By increasing the proportion of amorphous carbon, the balance between electromagnetic loss and impedance matching can be effectively maintained. Importantly, in a suitable graphitization environment, the presence of oxygen vacancies in amorphous carbon can induce significant polarization to compensate for the reduced conductivity loss due to the absence of sp2 carbon. Through the synergistic effects of morphology and composition, the samples exhibit a broader absorption bandwidth (6.28 GHz) and stronger reflection loss (−61.64 dB) compared to the original MOF. In conclusion, this study aims to elucidate the multiscale impacts of macroscopic micro-nano structure and microscopic defect engineering, providing valuable insights for future research in this field.展开更多
With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of...With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of multimodal approaches for fake news detection has gained significant attention.To solve the problems existing in previous multi-modal fake news detection algorithms,such as insufficient feature extraction and insufficient use of semantic relations between modes,this paper proposes the MFFFND-Co(Multimodal Feature Fusion Fake News Detection with Co-Attention Block)model.First,the model deeply explores the textual content,image content,and frequency domain features.Then,it employs a Co-Attention mechanism for cross-modal fusion.Additionally,a semantic consistency detectionmodule is designed to quantify semantic deviations,thereby enhancing the performance of fake news detection.Experimentally verified on two commonly used datasets,Twitter and Weibo,the model achieved F1 scores of 90.0% and 94.0%,respectively,significantly outperforming the pre-modified MFFFND(Multimodal Feature Fusion Fake News Detection with Attention Block)model and surpassing other baseline models.This improves the accuracy of detecting fake information in artificial intelligence detection and engineering software detection.展开更多
Objective:The objective of this study is to develop and evaluate a structured clinical rotation-based emergency response training program to enhance nurses’emergency competence,theoretical knowledge,and technical ski...Objective:The objective of this study is to develop and evaluate a structured clinical rotation-based emergency response training program to enhance nurses’emergency competence,theoretical knowledge,and technical skills.Methods:A comprehensive emergency training program was developed,and a randomized controlled trial was implemented from June 2022 to May 2023 at a tertiary general hospital in Chongqing,China.The study involved 214 nurses,with 106 participants in the intervention group receiving a 3-month innovative emergency response competence training and 108 in the control group undergoing conventional training.Postintervention assessments evaluated emergency response capabilities using the Emergency Response Ability Assessment Scale for Nurses in Public Health Emergencies,theoretical knowledge through a self-designed comprehensive theoretical assessment instrument,technical skills using a standardized skill assessment form,and training satisfaction through two distinct feedback instruments.Results:The emergency response ability scores were significantly higher in the intervention group compared to controls(3.99±0.18 vs.2.53±0.25,P<0.05).Theoretical assessment scores showed marked improvement in the intervention group versus the control group(85.31±4.40 vs.52.45±6.19,P<0.05).Technical skill performance was significantly better in the intervention group than that in controls(94.47±1.64 vs.86.39±2.36,P<0.05).Training satisfaction was higher among intervention group nurses compared to controls(4.53±0.23 vs.4.00±0.38,P<0.05),with nursing managers also reporting greater satisfaction with the intervention program versus conventional training(4.57±0.49 vs.3.92±0.79,P<0.05).Conclusion:The clinical rotation-based structured emergency response training program effectively enhances nurses’emergency competencies,theoretical knowledge,and technical skills.These findings provide both theoretical foundations and practical guidelines for developing emergency response and specialized nursing competence training programs.展开更多
基金Opening Foundation of Key Laboratory of Explosive Energy Utilization and Control,Anhui Province(BP20240104)Graduate Innovation Program of China University of Mining and Technology(2024WLJCRCZL049)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2701)。
文摘Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.
文摘软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。
基金supported by the Natural Science Foundation of China(Grant No.42302170)National Postdoctoral Innovative Talent Support Program(Grant No.BX20220062)+3 种基金CNPC Innovation Found(Grant No.2022DQ02-0104)National Science Foundation of Heilongjiang Province of China(Grant No.YQ2023D001)Postdoctoral Science Foundation of Heilongjiang Province of China(Grant No.LBH-Z22091)the Natural Science Foundation of Shandong Province(Grant No.ZR2022YQ30).
文摘Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some shortcomings because of the low permeability and tightness of shale,complex gas flow behavior of multi-scale gas transport regions and multiple gas transport mechanism superpositions,and complex and variable production regimes of shale gas wells.Recent research has demonstrated the existence of a multi-stage isotope fractionation phenomenon during shale gas production,with the fractionation characteristics of each stage associated with the pore structure,gas in place(GIP),adsorption/desorption,and gas production process.This study presents a new approach for estimating shale gas well production and evaluating the adsorbed/free gas ratio throughout production using isotope fractionation techniques.A reservoir-scale carbon isotope fractionation(CIF)model applicable to the production process of shale gas wells was developed for the first time in this research.In contrast to the traditional model,this model improves production prediction accuracy by simultaneously fitting the gas production rate and δ^(13)C_(1) data and provides a new evaluation method of the adsorbed/free gas ratio during shale gas production.The results indicate that the diffusion and adsorption/desorption properties of rock,bottom-hole flowing pressure(BHP)of gas well,and multi-scale gas transport regions of the reservoir all affect isotope fractionation,with the diffusion and adsorption/desorption parameters of rock having the greatest effect on isotope fractionation being D∗/D,PL,VL,α,and others in that order.We effectively tested the universality of the four-stage isotope fractionation feature and revealed a unique isotope fractionation mechanism caused by the superimposed coupling of multi-scale gas transport regions during shale gas well production.Finally,we applied the established CIF model to a shale gas well in the Sichuan Basin,China,and calculated the estimated ultimate recovery(EUR)of the well to be 3.33×10^(8) m^(3);the adsorbed gas ratio during shale gas production was 1.65%,10.03%,and 23.44%in the first,fifth,and tenth years,respectively.The findings are significant for understanding the isotope fractionation mechanism during natural gas transport in complex systems and for formulating and optimizing unconventional natural gas development strategies.
文摘BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential to mitigate these adverse effects and enhance overall health outcomes in this population.AIM To evaluate the effects of exercise-cognitive dual-task training on frailty,cognitive function,psychological status,and quality of life in elderly patients with cognitive frailty and depression.METHODS A retrospective study was conducted on 130 patients with cognitive frailty and depression admitted between December 2021 and December 2023.Patients were divided into a control group receiving routine intervention and an observation group undergoing exercise-cognitive dual-task training in addition to routine care.Frailty,cognitive function,balance and gait,psychological status,and quality of life were assessed before and after the intervention.RESULTS After the intervention,the frailty score of the observation group was(5.32±0.69),lower than that of the control group(5.71±0.55).The Montreal cognitive assessment basic scale score in the observation group was(24.06±0.99),higher than the control group(23.43±1.40).The performance oriented mobility assessment score in the observation group was(21.81±1.24),higher than the control group(21.15±1.26).The self-efficacy in the observation group was(28.27±2.66),higher than the control group(30.05±2.66).The anxiety score in the hospital anxiety and depression scale(HADS)for the observation group was(5.86±0.68),lower than the control group(6.21±0.64).The depression score in the HADS for the observation group was(5.67±0.75),lower than the control group(6.27±0.92).Additionally,the scores for each dimension of the 36-item short form survey in the observation group were higher than those in the control group,with statistically significant differences(P<0.05).CONCLUSION Exercise-cognitive dual-task training is beneficial for improving frailty,enhancing cognitive function,and improving psychological status and quality of life in elderly patients with cognitive frailty and depression.
基金supported by the National Natural Science Foundation of China(62272049,62236006,62172045)the Key Projects of Beijing Union University(ZKZD202301).
文摘In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金supported by the National Natural Science Foundation of China(Grant Nos.42150204 and 2288101)supported by the China National Postdoctoral Program for Innovative Talents(BX20230045)the China Postdoctoral Science Foundation(2023M730279)。
文摘A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.
文摘Exercise is a therapeutic approach in cancer treatment,providing several benefits.Moreover,exercise is associated with a reduced risk for developing a range of cancers and for their recurrence,as well as with improving survival,even though the underlying mechanisms remain unclear.Preclinical and clinical evidence shows that the acute effects of a single exercise session can suppress the growth of various cancer cell lines in vitro.This suppression is potentially due to altered concentrations of hormones(e.g.,insulin)and cytokines(e.g.,tumor necrosis factor alpha and interleukin 6)after exercise.These factors,known to be involved in tumorigenesis,may explain why exercise is associated with reduced cancer incidence,recurrence,and mortality.However,the effects of short-(<8 weeks)and long-term(≥8 weeks)exercise programs on cancer cells have been reported with mixed results.Although more research is needed,it appears that interventions incorporating both exercise and diet seem to have greater inhibitory effects on cancer cell growth in both apparently healthy subjects as well as in cancer patients.Although speculative,these suppressive effects on cancer cells may be driven by changes in body weight and composition as well as by a reduction in low-grade inflammation often associated with sedentary behavior,low muscle mass,and excess fat mass in cancer patients.Taken together,such interventions could alter the systemic levels of suppressive circulating factors,leading to a less favorable environment for tumorigenesis.While regular exercise and a healthy diet may establish a more cancer-suppressive environment,each acute bout of exercise provides a further“dose”of anticancer medicine.Therefore,integrating regular exercise could potentially play a significant role in cancer management,highlighting the need for future investigations in this promising area of research.
基金Research on the Construction of a Course Ideological and Political Education System and Evaluation Framework for the“Traditional Chinese Medicine Internal Medicine”Course(Project No.:2025J0459)Open Research Fund Program of Yunnan Key Laboratory of Integrated Traditional Chinese(Project No.:CWCD2023-002,CWCD2023-003&CWCD2023-009)+2 种基金Western Medicine for Chronic Disease in Prevention and TreatmentYunnan 047 Key Laboratory of Yi Dai Medicine and Yi Medicine(Project No.:2024SS24047)Yunnan 025 Key Laboratory of Yi Dai Medicine and Yi Medicine(Project No.:2024SS24025)。
文摘Standardized residency training programs primarily focus on developing clinical diagnostic and treatment skills,often allocating limited time to research activities.However,enhancing research skills is of paramount importance for residents,as it fosters critical thinking,problem-solving abilities,and a deeper understanding of applying scientific principles to clinical practice.This paper explores the necessity and significance of integrating research training into residency programs,emphasizing its role in cultivating well-rounded physicians capable of advancing medical knowledge.This study proposes a competency-based research training model that encompasses research literacy,study design,biostatistics,and scientific writing.Additionally,online asynchronous training modules,robust mentorship,and balanced time management strategies are recommended to enhance residents’research engagement without compromising clinical training.By implementing these measures,residency programs can improve residents’research capabilities,contributing to both individual professional growth and the broader advancement of medical science.
文摘Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhancement(endurance and sprints),and(b)the influence of participant characteristics and intervention protocols on these effects.Methods Searches were conducted in PubMed,Web of Science(Core Collection),Cochrane Library(Embase,ClinicalTrials.gov,and International Clinical Trials Registry Platform),and Chinese National Knowledge Infrastructure on April 2,with updates on October 17,2024.Pooled effects for each outcome were summarized using Hedge's g(g)through meta-analysis-based random effects models,and subgroup and regression analyses were used to explore moderators.Results A total of 24 studies with 621 participants were included.IT combined with BFR(IT+BFR)significantly improved maximal oxygen uptake(VO2_(max))(g=0.63,I^(2)=63%),mean power during the Wingate 30-s test(g=0.70,I^(2)=47%),muscle strength(g=0.88,I^(2)=64%),muscle endurance(g=0.43,I^(2)=0%),time to fatigue(g=1.26,I^(2)=86%),and maximal aerobic speed(g=0.74,I^(2)=0%)compared to IT alone.Subgroup analysis indicated that participant characteristics including training status,IT intensity,and IT modes significantly moderated VO2_(max)(subgroup differences:p<0.05).Specifically,IT+BFR showed significantly superior improvements in VO2_(max)compared to IT alone in trained individuals(g=0.76)at supra-maximal intensity(g=1.29)and moderate intensity(g=1.08)as well as in walking(g=1.64)and running(g=0.63)modes.Meta-regression analysis showed cuff width(β=0.14)was significantly associated with VO2_(max)change,identifying 8.23 cm as the minimum threshold required for significant improvement.Subgroup analyses regarding muscle strength did not reveal any significant moderators.Conclusion IT+BFR enhances physiological adaptations and optimizes aspects of endurance performance,with moderators including training status,IT protocol(intensity,mode,and type),and cuff width.This intervention addresses various IT-related challenges and provides tailored protocols and benefits for diverse populations.
文摘Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a continuous challenge university managers face.To explore a method of preventing psychological crises among college students,we measured 38661 students by using SCL-90(symptom check list-90)and screened out 5790 students with positive results.Then,we measured 33188 students by using PHQ-9(patient health questionnaire-9)and screened out 603 students with suicidal ideation or behavior;we interviewed 392 students by using GAQ(growth adversity questionnaire).The number of students who had positive results at both phases is 155.As a result,we obtained a data set(N=76)by integrating the students who tested positive on the PHQ-9(i.e.total score≥20)with those who completed the PHQ-9 and GAQ.In addition,we obtained a data set(N=50)by excluding the cases in which the GAQ score is 0.With regard to QCA(qualitative comparative analysis)results,the data set(N=76)exhibits 5 constellations of solutions with a coverage rate greater than 0.7,and the first eight indicators of the PHQ-9 constitute the explanatory variables in the combined solutions.About the data set(N=50),the combined solutions are extremely complicated and the explanatory variables encompass indicators from both the PHQ-9 and GAQ.All these mean that the multi-scale could more comprehensively reflect mental health states of college students,thus enhance the accuracy and effectiveness of the corresponding hierarchical intervention,and finally provide support for preventing psychological crises in universities.
基金Teaching and Research Project of Anhui Urban Management Vocational College(Project No.:2024kfkc001)。
文摘This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessment Form has been assessed as severe articulation disorder.The patient has significantly improved his speech function and quality of life after systematic head control training,respiratory function training,articulation motor training,and articulation training.In the course of treatment,emphasis was placed on head postural control training and respiratory function training,and emphasis was placed on the strength and coordination training of articulatory organs,and the results were remarkable.After the patient was discharged from the hospital,the follow-up of basic daily life communication was not limited.
基金supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.15308024)a grant from Research Centre for Carbon-Strategic Catalysis,The Hong Kong Polytechnic University(CE2X).
文摘Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.
基金supported by a grant from University of Social Welfare and Rehabilitation Sciences for the research expenses.
文摘Background Schizophrenia is characterised by pervasive cognitive deficits that significantly impair daily functioning and quality of life.Pharmacological treatments have limited efficacy in addressing these deficits,highlighting the need for adjunctive interventions like computerised cognitive training(CCT).Aims This study aimed to evaluate the effects of a 30-session CCT programme on mental well-being and cognitive performance in individuals with schizophrenia.Additionally,it assessed the usability and acceptability of CCT in this population.Methods A double-blind,randomised clinical trial was conducted with 54 participants assigned to intervention and control groups.Cognitive and mental health outcomes were assessed using validated tools such as the Depression Anxiety Stress Scale 21,the Warwick-Edinburgh Mental Wellbeing Scale and the Cambridge Neuropsychological Test Automated Battery.Usability was measured with the System Usability Scale(SUS).Assessments were conducted at baseline,post-intervention and 3 months post-follow-up.Results The CCT intervention significantly improved mental well-being,reduced stress and enhanced working memory(paired associate learning,spatial working memory and spatial span)compared with controls.However,no significant effects were observed for anxiety,depression or executive function.Usability scores were high(SUS=83.51),and compliance rates were strong(92.7%),indicating favourable participant engagement.Conclusion CCT demonstrated potential as an adjunctive treatment for schizophrenia,with significant improvements in targeted cognitive and mental health domains.The high usability and compliance rates support its feasibility for broader implementation.Further research is needed to optimise protocols and explore long-term benefits.CCT offers a promising approach to addressing mental health and cognitive challenges in schizophrenia,particularly for stress and working memory.Its usability and acceptability suggest it could be seamlessly integrated into clinical practice.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
基金funded by the China Chongqing Municipal Science and Technology Bureau,grant numbers 2024TIAD-CYKJCXX0121,2024NSCQ-LZX0135Chongqing Municipal Commission of Housing and Urban-Rural Development,grant number CKZ2024-87+3 种基金the Chongqing University of Technology graduate education high-quality development project,grant number gzlsz202401the Chongqing University of Technology-Chongqing LINGLUE Technology Co.,Ltd.,Electronic Information(Artificial Intelligence)graduate joint training basethe Postgraduate Education and Teaching Reform Research Project in Chongqing,grant number yjg213116the Chongqing University of Technology-CISDI Chongqing Information Technology Co.,Ltd.,Computer Technology graduate joint training base.
文摘Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells and the significant variations in cell size.Pathologists often refer to surrounding cells to identify abnormalities.To emulate this slide examination behavior,this study proposes a Multi-Scale Feature Fusion Network(MSFF-Net)for detecting cervical abnormal cells.MSFF-Net employs a Cross-Scale Pooling Model(CSPM)to effectively capture diverse features and contextual information,ranging from local details to the overall structure.Additionally,a Multi-Scale Fusion Attention(MSFA)module is introduced to mitigate the impact of cell size variations by adaptively fusing local and global information at different scales.To handle the complex environment of cervical cell images,such as cell adhesion and overlapping,the Inner-CIoU loss function is utilized to more precisely measure the overlap between bounding boxes,thereby improving detection accuracy in such scenarios.Experimental results on the Comparison detector dataset demonstrate that MSFF-Net achieves a mean average precision(mAP)of 63.2%,outperforming state-of-the-art methods while maintaining a relatively small number of parameters(26.8 M).This study highlights the effectiveness of multi-scale feature fusion in enhancing the detection of cervical abnormal cells,contributing to more accurate and efficient cervical cancer screening.
基金supported by the National Natural Science Foundation of China(52172091,52172295)Defense Industrial Technology Development Program(JCKY2023605C002)+4 种基金Frontier Leading Technology Basic Research Major Project of Jiangsu Province(SBK2023050110)the National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering(NO.61422062301)the Opening Project of Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory(ZHD202305)the Opening Project of Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology(ASMA202303)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0371).
文摘Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distinguishing the MA contributions of different scale factors and tuning the optimal combined effects remains a formidable challenge. This study employs a synergistic approach combining template protection etching and vacuum annealing to construct a controlled system of micrometer-sized cavities and amorphous carbon matrices in metal-organic framework (MOF) derivatives. The results demonstrate that the spatial effects introduced by the hollow structure enhance dielectric loss but significantly weaken impedance matching. By increasing the proportion of amorphous carbon, the balance between electromagnetic loss and impedance matching can be effectively maintained. Importantly, in a suitable graphitization environment, the presence of oxygen vacancies in amorphous carbon can induce significant polarization to compensate for the reduced conductivity loss due to the absence of sp2 carbon. Through the synergistic effects of morphology and composition, the samples exhibit a broader absorption bandwidth (6.28 GHz) and stronger reflection loss (−61.64 dB) compared to the original MOF. In conclusion, this study aims to elucidate the multiscale impacts of macroscopic micro-nano structure and microscopic defect engineering, providing valuable insights for future research in this field.
基金supported by Communication University of China(HG23035)partly supported by the Fundamental Research Funds for the Central Universities(CUC230A013).
文摘With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of multimodal approaches for fake news detection has gained significant attention.To solve the problems existing in previous multi-modal fake news detection algorithms,such as insufficient feature extraction and insufficient use of semantic relations between modes,this paper proposes the MFFFND-Co(Multimodal Feature Fusion Fake News Detection with Co-Attention Block)model.First,the model deeply explores the textual content,image content,and frequency domain features.Then,it employs a Co-Attention mechanism for cross-modal fusion.Additionally,a semantic consistency detectionmodule is designed to quantify semantic deviations,thereby enhancing the performance of fake news detection.Experimentally verified on two commonly used datasets,Twitter and Weibo,the model achieved F1 scores of 90.0% and 94.0%,respectively,significantly outperforming the pre-modified MFFFND(Multimodal Feature Fusion Fake News Detection with Attention Block)model and surpassing other baseline models.This improves the accuracy of detecting fake information in artificial intelligence detection and engineering software detection.
基金supported by a research grant from the Medical Research Program of Chongqing University Three Gorges Hospital(No.2022YJKYXM-017).
文摘Objective:The objective of this study is to develop and evaluate a structured clinical rotation-based emergency response training program to enhance nurses’emergency competence,theoretical knowledge,and technical skills.Methods:A comprehensive emergency training program was developed,and a randomized controlled trial was implemented from June 2022 to May 2023 at a tertiary general hospital in Chongqing,China.The study involved 214 nurses,with 106 participants in the intervention group receiving a 3-month innovative emergency response competence training and 108 in the control group undergoing conventional training.Postintervention assessments evaluated emergency response capabilities using the Emergency Response Ability Assessment Scale for Nurses in Public Health Emergencies,theoretical knowledge through a self-designed comprehensive theoretical assessment instrument,technical skills using a standardized skill assessment form,and training satisfaction through two distinct feedback instruments.Results:The emergency response ability scores were significantly higher in the intervention group compared to controls(3.99±0.18 vs.2.53±0.25,P<0.05).Theoretical assessment scores showed marked improvement in the intervention group versus the control group(85.31±4.40 vs.52.45±6.19,P<0.05).Technical skill performance was significantly better in the intervention group than that in controls(94.47±1.64 vs.86.39±2.36,P<0.05).Training satisfaction was higher among intervention group nurses compared to controls(4.53±0.23 vs.4.00±0.38,P<0.05),with nursing managers also reporting greater satisfaction with the intervention program versus conventional training(4.57±0.49 vs.3.92±0.79,P<0.05).Conclusion:The clinical rotation-based structured emergency response training program effectively enhances nurses’emergency competencies,theoretical knowledge,and technical skills.These findings provide both theoretical foundations and practical guidelines for developing emergency response and specialized nursing competence training programs.
