This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawin...Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawings, documentation and the like are still incomplete. As such, various techniques have been applied to accurately estimate construction costs at an early stage, when project information is limited. While the various techniques have their pros and cons, there has been little effort made to determine the best technique in terms of cost estimating performance. The objective of this research is to compare the accuracy of three estimating techniques (regression analysis (RA), neural network (NN), and support vector machine techniques (SVM)) by performing estimations of construction costs. By comparing the accuracy of these techniques using historical cost data, it was found that NN model showed more accurate estimation results than the RA and SVM models. Consequently, it is determined that NN model is most suitable for estimating the cost of school building projects.展开更多
Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to p...Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.展开更多
Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims ...Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.展开更多
Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev...Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.展开更多
Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dep...Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.展开更多
The idea of a network society was introduced by Western sociologists at the end of the 20th century after in-depth research was conducted from perspectives such as informationalism.Influenced by these developments,the...The idea of a network society was introduced by Western sociologists at the end of the 20th century after in-depth research was conducted from perspectives such as informationalism.Influenced by these developments,the concept of constructing a network society also emerged in China.Over the past 30 years,China has made significant progress and achievements in constructing a network society,both in terms of its fundamental construction and social development.It is important that these advancements be summarized and reviewed.China’s network society construction can be divided into two relatively independent yet interconnected components,based on their focal points:its foundational infrastructure and its social development.These two components of China’s network society are managed by different departments.China has integrated the fundamental construction of its network society with the social development of its network society,thereby achieving unified planning,collaborative advancement,and coordinated development.This approach aims to harmonize two aspects:building China’s cyberspace strength and contributing to Chinese informatization,thereby advancing Chinese modernization.展开更多
The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlatio...The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.展开更多
Green building construction typically incurs higher costs than conventional methods.To facilitate broader adoption by construction entities,cost optimization is essential.Firms must align with technological advancemen...Green building construction typically incurs higher costs than conventional methods.To facilitate broader adoption by construction entities,cost optimization is essential.Firms must align with technological advancements,judiciously apply emerging technologies,and ensure resource efficiency through context-specific strategies.Proactive and precise scheduling is critical to avert delays from unforeseen events.Additionally,construction units should enhance on-site safety training,promote mastery of innovative techniques,and foster environmental awareness among personnel.Finally,companies ought to capitalize on government incentives for green materials while adopting bulk procurement from local sources to minimize transportation costs and secure lower unit prices.展开更多
Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study...Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.展开更多
Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.How...Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.展开更多
Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese ver...Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese version of the CAQ-8 along with other standardized measures,including the Acceptance and Action Questionnaire-II(AAQ-II),the Valuing Questionnaire(VQ),the Satisfaction with Life Scale(SWLS),the Depression Anxiety Stress Scales(DASS-21),and the World Health Organization Fiveitem Well-Being Index(WHO-5).A retest was conducted one month later with 300 valid responses.Results:Exploratory factor analysis(n=818)identified a 2-factor structure,confirmed through validated factor analysis(n=817),showing good fit indices(CFI=0.990,RMSEA=0.040).Measurement equivalence across genders was established.The CAQ-8 showed significant positive correlations with life satisfaction,mental health,and values,and negative correlations with depression,anxiety,stress,and experiential avoidance.The scale demonstrated good internal consistency(Cronbach’sα=0.76)and retest reliability(ICC=0.70).Network analysis confirmed the robustness of the 2-factor model,with item 4 in CAQ-8 identified as a core item.Conclusion:The CAQ-8 is a reliable and valid tool for measuring committed action within the psychological flexibility model in Chinese populations.展开更多
Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to ful...Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to fully prevent heat stress with an urgent need to develop preventive medicines.The aim of this study was to develop an antiheat stress Chinese herbal formula(CHF)via big data analysis techniques and to evaluate its anti-heat stress effect and mechanism of action via pharmacodynamic evaluation and network pharmacology analysis.Many anti-heat stress CHFs were collected from the Chinese National Knowledge Infrastructure(CNKI)database.Three alternative CHFs were obtained via unsupervised entropy hierarchical clustering analysis,and the most effective CHF against heat stress,Shidi Jieshu decoction(SJD),was obtained by screening in a mouse heat stress model.In dry and hot environments,SJD significantly improved the heat tolerance of AA broilers by 4-6℃.In a humid and hot environment,pretreatment with 2%SJD resulted in 100%survival of Wenchang chickens at high temperatures.The main active ingredients of SJD were identified as muntjacoside E,timosaponin C,macrostemonoside H and mangiferin via ultraperformance liquid chromatography/mass spectrometry(UPLC/MS)and database comparison.The active ingredients of SJD were found to target tumor necrosis factor-α(TNF-α),signal transducer activator of transcription 3(STAT3)and epidermal growth factor receptor(EGFR).Finally,the safety of the new formulation was assessed in an acute oral toxicity study in rats.The SJDs developed in this study provide a new option for the prevention of heat stress in animal husbandry and offer new insights for further research on anti-heat stress.展开更多
Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analy...Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.展开更多
BACKGROUND Depression and anxiety are prevalent psychological challenges among patients with adolescent idiopathic scoliosis(AIS),affecting individuals across both sex and age groups.AIM To explore the network structu...BACKGROUND Depression and anxiety are prevalent psychological challenges among patients with adolescent idiopathic scoliosis(AIS),affecting individuals across both sex and age groups.AIM To explore the network structure of depression and anxiety symptoms,with a focus on identifying differences at the symptom level between sex and age subgroups.METHODS A total of 1955 participants diagnosed with AIS aged 10-18 years were assessed using the Patient Health Questionnaire Depression Scale(PHO-9)and the Generalized Anxiety Disorder Scale(GAD-7),and 765 patients exhibiting PHQ-9 or GAD-7 scores ≥ 5 were enrolled in our study. Network analysis and network comparison tests were utilized toconstruct and compare the depression-anxiety symptoms networks among sex and age subgroups.RESULTSThe results revealed GAD3 “Excessive worry” and PHQ2 “Sad mood” were the most significant central symptomsin all subgroups, while “Sad mood” had higher strength than “Excessive worry” in the lower age group. In thenetwork comparisons, the female network exhibited tighter connectivity, especially on GAD6 “Irritability” andGAD2 “Uncontrollable worry”, while only PHQ3 “Sleep” and PHQ9 “Suicidal ideation” had differences at thelocal level in the lower age group.CONCLUSIONSeveral interventions targeting excessive worry and sad mood could reduce the risk of depression and anxietysymptoms in the AIS population. Furthermore, specific anxiety symptoms in females, along with sleep disturbancesand suicidal ideation in the lower age group, should be addressed at an early stage to prevent significantdisruptions in mental health trajectories.展开更多
With the increasing importance of multimodal data in emotional expression on social media,mainstream methods for sentiment analysis have shifted from unimodal to multimodal approaches.However,the challenges of extract...With the increasing importance of multimodal data in emotional expression on social media,mainstream methods for sentiment analysis have shifted from unimodal to multimodal approaches.However,the challenges of extracting high-quality emotional features and achieving effective interaction between different modalities remain two major obstacles in multimodal sentiment analysis.To address these challenges,this paper proposes a Text-Gated Interaction Network with Inter-Sample Commonality Perception(TGICP).Specifically,we utilize a Inter-sample Commonality Perception(ICP)module to extract common features from similar samples within the same modality,and use these common features to enhance the original features of each modality,thereby obtaining a richer and more complete multimodal sentiment representation.Subsequently,in the cross-modal interaction stage,we design a Text-Gated Interaction(TGI)module,which is text-driven.By calculating the mutual information difference between the text modality and nonverbal modalities,the TGI module dynamically adjusts the influence of emotional information from the text modality on nonverbal modalities.This helps to reduce modality information asymmetry while enabling full cross-modal interaction.Experimental results show that the proposed model achieves outstanding performance on both the CMU-MOSI and CMU-MOSEI baseline multimodal sentiment analysis datasets,validating its effectiveness in emotion recognition tasks.展开更多
In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shi...In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.展开更多
To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate ...To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.展开更多
Construction 3D printing is changing construction industry, but for its immaturity, there are still many problems to be solved. One of the major problems is to study materials for construction 3D printing. Because pri...Construction 3D printing is changing construction industry, but for its immaturity, there are still many problems to be solved. One of the major problems is to study materials for construction 3D printing. Because printed buildings are very different from traditional buildings, there are special requirements for printing materials. Based on environmental and cost considerations, the recycled concrete as printing material is a perfect choice. In order to study and develop the construction 3D printing materials, it is necessary to predict the properties of them. As one of the most effective artificial intelligence algorithms, artificial neural network can deal with multi-parameter and nonlinear problems, and it can provide useful reference to predict the performance of recycled concrete for 3D printing. However, since there are many types and parameters for neural network, it is difficult to select the optimal neural network with excellent prediction performance. In this paper, by comparing different types of neural networks and statistically analyzing the distribution of the root-mean-square error (RMSE) and the coefficient of determination (R2) of these neural networks, we can determine the best performance among four neural networks and finally select the suitable one to predict the performance of 3D printing concrete.展开更多
β-ray-induced X-ray spectroscopy(BIXS)is a promising technique for tritium analysis that offers several unique advantages,including substantial detection depth,nondestructive testing capabilities,and ease of operatio...β-ray-induced X-ray spectroscopy(BIXS)is a promising technique for tritium analysis that offers several unique advantages,including substantial detection depth,nondestructive testing capabilities,and ease of operation.For thin solid tritium-containing samples with substrates,the currently used BIXS analysis method can measure the tritium depth profile and content when the sample thickness is known.In this study,a backpropagation(BP)neural network algorithm was used to predict the tritium content and thickness of a thin solid tritium-containing sample with substrates and a uniformly distributed tritium profile.A semi-analytical method was used to generate datasets for training and testing the BP neural network.A dataset ofβ-decay X-ray spectra from 420 tritium-containing zirconium models with different known thicknesses and tritium-tozirconium ratios was used as the input data.The corresponding zirconium thicknesses and tritium-to-zirconium ratios served as the output for training and testing the BP neural network.The mean relative errors(MREs)of the zirconium thickness in the training and test datasets were 0.56%and 0.42%,respectively,whereas the MREs of the tritium-to-zirconium ratio were 0.59%and 0.38%,respectively.Furthermore,the trained BP neural network demonstrates excellent predictive capability across various levels of statistical uncertainty.For the experimentalβ-decay X-ray spectra of two tritium-containing samples,the predicted zirconium thicknesses and tritium-to-zirconium ratios showed good agreement with the results obtained through the elastic backscattering spectrometry(EBS).展开更多
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
文摘Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawings, documentation and the like are still incomplete. As such, various techniques have been applied to accurately estimate construction costs at an early stage, when project information is limited. While the various techniques have their pros and cons, there has been little effort made to determine the best technique in terms of cost estimating performance. The objective of this research is to compare the accuracy of three estimating techniques (regression analysis (RA), neural network (NN), and support vector machine techniques (SVM)) by performing estimations of construction costs. By comparing the accuracy of these techniques using historical cost data, it was found that NN model showed more accurate estimation results than the RA and SVM models. Consequently, it is determined that NN model is most suitable for estimating the cost of school building projects.
基金supported by the Specific Research Fund for Top-notch Talents of Guangdong Provincial Hospital of Chinese Medicine(No.2022KT1188).
文摘Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.
基金supported by the National Natural Science Foundation of China(Grant No.72364006).
文摘Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.
基金supported by the National Natural Science Foundation of China,Nos.81871836(to MZ),82172554(to XH),and 81802249(to XH),81902301(to JW)the National Key R&D Program of China,Nos.2018YFC2001600(to JX)and 2018YFC2001604(to JX)+3 种基金Shanghai Rising Star Program,No.19QA1409000(to MZ)Shanghai Municipal Commission of Health and Family Planning,No.2018YQ02(to MZ)Shanghai Youth Top Talent Development PlanShanghai“Rising Stars of Medical Talent”Youth Development Program,No.RY411.19.01.10(to XH)。
文摘Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.
文摘Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.
基金“Research on Social Change and Network Society Planning in the Internet of Everything Era”(ID:21BSH005),a project under the National Social Science Fund of China
文摘The idea of a network society was introduced by Western sociologists at the end of the 20th century after in-depth research was conducted from perspectives such as informationalism.Influenced by these developments,the concept of constructing a network society also emerged in China.Over the past 30 years,China has made significant progress and achievements in constructing a network society,both in terms of its fundamental construction and social development.It is important that these advancements be summarized and reviewed.China’s network society construction can be divided into two relatively independent yet interconnected components,based on their focal points:its foundational infrastructure and its social development.These two components of China’s network society are managed by different departments.China has integrated the fundamental construction of its network society with the social development of its network society,thereby achieving unified planning,collaborative advancement,and coordinated development.This approach aims to harmonize two aspects:building China’s cyberspace strength and contributing to Chinese informatization,thereby advancing Chinese modernization.
文摘The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.
文摘Green building construction typically incurs higher costs than conventional methods.To facilitate broader adoption by construction entities,cost optimization is essential.Firms must align with technological advancements,judiciously apply emerging technologies,and ensure resource efficiency through context-specific strategies.Proactive and precise scheduling is critical to avert delays from unforeseen events.Additionally,construction units should enhance on-site safety training,promote mastery of innovative techniques,and foster environmental awareness among personnel.Finally,companies ought to capitalize on government incentives for green materials while adopting bulk procurement from local sources to minimize transportation costs and secure lower unit prices.
基金financed by the grants from the National Natural Science Foundation of China(No.81803996)Shanghai Key Laboratory of Health Identification and Assessment(No.21DZ2271000)。
文摘Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.
文摘Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.
文摘Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese version of the CAQ-8 along with other standardized measures,including the Acceptance and Action Questionnaire-II(AAQ-II),the Valuing Questionnaire(VQ),the Satisfaction with Life Scale(SWLS),the Depression Anxiety Stress Scales(DASS-21),and the World Health Organization Fiveitem Well-Being Index(WHO-5).A retest was conducted one month later with 300 valid responses.Results:Exploratory factor analysis(n=818)identified a 2-factor structure,confirmed through validated factor analysis(n=817),showing good fit indices(CFI=0.990,RMSEA=0.040).Measurement equivalence across genders was established.The CAQ-8 showed significant positive correlations with life satisfaction,mental health,and values,and negative correlations with depression,anxiety,stress,and experiential avoidance.The scale demonstrated good internal consistency(Cronbach’sα=0.76)and retest reliability(ICC=0.70).Network analysis confirmed the robustness of the 2-factor model,with item 4 in CAQ-8 identified as a core item.Conclusion:The CAQ-8 is a reliable and valid tool for measuring committed action within the psychological flexibility model in Chinese populations.
基金supported by the Major Special Science and Technology Plan(202302AA310020)the National Natural Science Foundation of China(NSFC)(32072925,32473087)the National Student Innovation and Entrepreneurship Training Program of Huazhong Agricultural University(202310504018)。
文摘Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to fully prevent heat stress with an urgent need to develop preventive medicines.The aim of this study was to develop an antiheat stress Chinese herbal formula(CHF)via big data analysis techniques and to evaluate its anti-heat stress effect and mechanism of action via pharmacodynamic evaluation and network pharmacology analysis.Many anti-heat stress CHFs were collected from the Chinese National Knowledge Infrastructure(CNKI)database.Three alternative CHFs were obtained via unsupervised entropy hierarchical clustering analysis,and the most effective CHF against heat stress,Shidi Jieshu decoction(SJD),was obtained by screening in a mouse heat stress model.In dry and hot environments,SJD significantly improved the heat tolerance of AA broilers by 4-6℃.In a humid and hot environment,pretreatment with 2%SJD resulted in 100%survival of Wenchang chickens at high temperatures.The main active ingredients of SJD were identified as muntjacoside E,timosaponin C,macrostemonoside H and mangiferin via ultraperformance liquid chromatography/mass spectrometry(UPLC/MS)and database comparison.The active ingredients of SJD were found to target tumor necrosis factor-α(TNF-α),signal transducer activator of transcription 3(STAT3)and epidermal growth factor receptor(EGFR).Finally,the safety of the new formulation was assessed in an acute oral toxicity study in rats.The SJDs developed in this study provide a new option for the prevention of heat stress in animal husbandry and offer new insights for further research on anti-heat stress.
基金supported by the National Natural Science Foundation of China(72271242)Hunan Provincial Natural Science Foundation of China for Excellent Young Scholars(2022JJ20046).
文摘Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.
基金Supported by The Sanming Project of Medicine in Shenzhen,No.SZSM202211003Shenzhen-Hong Kong Jointly Funded Project,Shenzhen Science and Technology Program,No.SGDX20230116093645007+1 种基金Shenzhen Second People's Hospital Clinical Project,No.20243357003Shenzhen Medical Research Fund,No.B2303005.
文摘BACKGROUND Depression and anxiety are prevalent psychological challenges among patients with adolescent idiopathic scoliosis(AIS),affecting individuals across both sex and age groups.AIM To explore the network structure of depression and anxiety symptoms,with a focus on identifying differences at the symptom level between sex and age subgroups.METHODS A total of 1955 participants diagnosed with AIS aged 10-18 years were assessed using the Patient Health Questionnaire Depression Scale(PHO-9)and the Generalized Anxiety Disorder Scale(GAD-7),and 765 patients exhibiting PHQ-9 or GAD-7 scores ≥ 5 were enrolled in our study. Network analysis and network comparison tests were utilized toconstruct and compare the depression-anxiety symptoms networks among sex and age subgroups.RESULTSThe results revealed GAD3 “Excessive worry” and PHQ2 “Sad mood” were the most significant central symptomsin all subgroups, while “Sad mood” had higher strength than “Excessive worry” in the lower age group. In thenetwork comparisons, the female network exhibited tighter connectivity, especially on GAD6 “Irritability” andGAD2 “Uncontrollable worry”, while only PHQ3 “Sleep” and PHQ9 “Suicidal ideation” had differences at thelocal level in the lower age group.CONCLUSIONSeveral interventions targeting excessive worry and sad mood could reduce the risk of depression and anxietysymptoms in the AIS population. Furthermore, specific anxiety symptoms in females, along with sleep disturbancesand suicidal ideation in the lower age group, should be addressed at an early stage to prevent significantdisruptions in mental health trajectories.
基金supported by the Natural Science Foundation of Henan under Grant 242300421220the Henan Provincial Science and Technology Research Project under Grants 252102211047 and 252102211062+3 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126.
文摘With the increasing importance of multimodal data in emotional expression on social media,mainstream methods for sentiment analysis have shifted from unimodal to multimodal approaches.However,the challenges of extracting high-quality emotional features and achieving effective interaction between different modalities remain two major obstacles in multimodal sentiment analysis.To address these challenges,this paper proposes a Text-Gated Interaction Network with Inter-Sample Commonality Perception(TGICP).Specifically,we utilize a Inter-sample Commonality Perception(ICP)module to extract common features from similar samples within the same modality,and use these common features to enhance the original features of each modality,thereby obtaining a richer and more complete multimodal sentiment representation.Subsequently,in the cross-modal interaction stage,we design a Text-Gated Interaction(TGI)module,which is text-driven.By calculating the mutual information difference between the text modality and nonverbal modalities,the TGI module dynamically adjusts the influence of emotional information from the text modality on nonverbal modalities.This helps to reduce modality information asymmetry while enabling full cross-modal interaction.Experimental results show that the proposed model achieves outstanding performance on both the CMU-MOSI and CMU-MOSEI baseline multimodal sentiment analysis datasets,validating its effectiveness in emotion recognition tasks.
基金supported by the National Natural Science Foundation of China(No.62027801).
文摘In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.
基金the research project funded by the Fundamental Research Funds for the Central Universities(No.HIT.OCEP.2024038)the National Natural Science Foundation of China(No.52372351)the State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster,China(No.MS02240107)。
文摘To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.
文摘Construction 3D printing is changing construction industry, but for its immaturity, there are still many problems to be solved. One of the major problems is to study materials for construction 3D printing. Because printed buildings are very different from traditional buildings, there are special requirements for printing materials. Based on environmental and cost considerations, the recycled concrete as printing material is a perfect choice. In order to study and develop the construction 3D printing materials, it is necessary to predict the properties of them. As one of the most effective artificial intelligence algorithms, artificial neural network can deal with multi-parameter and nonlinear problems, and it can provide useful reference to predict the performance of recycled concrete for 3D printing. However, since there are many types and parameters for neural network, it is difficult to select the optimal neural network with excellent prediction performance. In this paper, by comparing different types of neural networks and statistically analyzing the distribution of the root-mean-square error (RMSE) and the coefficient of determination (R2) of these neural networks, we can determine the best performance among four neural networks and finally select the suitable one to predict the performance of 3D printing concrete.
基金supported by the National Natural Science Foundation of China(No.12175158)the Institute of Nuclear Physics and Chemistry,China Academy of Engineering Physics(No.HG2022022)。
文摘β-ray-induced X-ray spectroscopy(BIXS)is a promising technique for tritium analysis that offers several unique advantages,including substantial detection depth,nondestructive testing capabilities,and ease of operation.For thin solid tritium-containing samples with substrates,the currently used BIXS analysis method can measure the tritium depth profile and content when the sample thickness is known.In this study,a backpropagation(BP)neural network algorithm was used to predict the tritium content and thickness of a thin solid tritium-containing sample with substrates and a uniformly distributed tritium profile.A semi-analytical method was used to generate datasets for training and testing the BP neural network.A dataset ofβ-decay X-ray spectra from 420 tritium-containing zirconium models with different known thicknesses and tritium-tozirconium ratios was used as the input data.The corresponding zirconium thicknesses and tritium-to-zirconium ratios served as the output for training and testing the BP neural network.The mean relative errors(MREs)of the zirconium thickness in the training and test datasets were 0.56%and 0.42%,respectively,whereas the MREs of the tritium-to-zirconium ratio were 0.59%and 0.38%,respectively.Furthermore,the trained BP neural network demonstrates excellent predictive capability across various levels of statistical uncertainty.For the experimentalβ-decay X-ray spectra of two tritium-containing samples,the predicted zirconium thicknesses and tritium-to-zirconium ratios showed good agreement with the results obtained through the elastic backscattering spectrometry(EBS).
