Analysis of level structure and monopole effects in Ca isotopes

Understanding the properties of nuclei near the double magic nucleus^(40)Ca is crucial for both nuclear theory and experiments.In this study,Ca isotopes were investigated using an extended pairing-plus-quadrupole model with monopole corrections.The negative-parity states of^(44)Ca were coupled with the intruder orbital g_(9/2)at 4 MeV.The values of E_(4+)/E_(2+)agree well with experimental trend from^(42)Ca to^(50)Ca,considering monopole effects between νf_(7/2)and νp_(3/2)(νf_(5/2)).This monopole effect,determined from data of^(48)Ca and^(50)Ca,supports the proposed new nuclear magic number N=34 by predicting a high-energy 2^(+)state in^(54)Ca.

The effects of population aging on industrial structure upgrading:Empirical analysis of provincial and threshold characteristics in China

Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographic aging,posing significant questions about its impact on the ongoing upgrading of industrial structures.How does this demographic shift influence the upgrading of industrial structures,and does technological innovation mitigate or exacerbate this impact?The empirical results indicate that population aging impedes upgrading the industrial structure,while technological innovation positively affects the relationship between the two.Moreover,using technological innovation as a threshold variable,the impact of population aging on industrial structure upgrading evolves in a“gradient”manner from“impediment”to“insignificant”to“promotion”as the technological innovation levels increase.These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.

Contour tracking using weighted structure tensor based variational level set

A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite symmetric covariance matrix for each pixel.Then,a level set method is employed to represent object contour implicitly which separates the image domain into two areas each modeled by tensor field based Gaussian mixture model separately.By solving agradient flow equation of energy functional with respect to the level set,the object contour will converge to its real profile in the newly arrived frame.Experimental results on several video sequences demonstrate the better performance of our method than the other two contour tracking algorithms.

Storyline Extraction of Document-Level Events Using Large Language Models

This article proposes a document-level prompt learning approach using LLMs to extract the timeline-based storyline. Through verification tests on datasets such as ESCv1.2 and Timeline17, the results show that the prompt + one-shot learning proposed in this article works well. Meanwhile, our research findings indicate that although timeline-based storyline extraction has shown promising prospects in the practical applications of LLMs, it is still a complex natural language processing task that requires further research.

A Multilevel Secure Relation-Hierarchical Data Model for a Secure DBMS

A multilevel secure relation hierarchical data model for multilevel secure database is extended from the relation hierarchical data model in single level environment in this paper. Based on the model, an upper lower layer relationalintegrity is presented after we analyze and eliminate the covert channels caused by the database integrity.Two SQL statements are extended to process polyinstantiation in the multilevel secure environment.The system based on the multilevel secure relation hierarchical data model is capable of integratively storing and manipulating complicated objects ( e.g. , multilevel spatial data) and conventional data ( e.g. , integer, real number and character string) in multilevel secure database.

Change in self-image pressure level before and after autologous fat breast augmentation and its effect on social adaptability

BACKGROUND There is an increasingly strong demand for appearance and physical beauty in social life,marriage,and other aspects with the development of society and the improvement of material living standards.An increasing number of people have improved their appearance and physical shape through aesthetic plastic surgery.The female breast plays a significant role in physical beauty,and droopy or atrophied breasts can frequently lead to psychological inferiority and lack of confidence in women.This,in turn,can affect their mental health and quality of life.AIM To analyze preoperative and postoperative self-image pressure-level changes of autologous fat breast augmentation patients and their impact on social adaptability.METHODS We selected 160 patients who underwent autologous fat breast augmentation at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to December 2022 using random sampling method.The general information,selfimage pressure level,and social adaptability of the patients were investigated using a basic information survey,body image self-assessment scale,and social adaptability scale.The self-image pressure-level changes and their effects on the social adaptability of patients before and after autologous fat breast augmentation were analyzed.RESULTS We collected 142 valid questionnaires.The single-factor analysis results showed no statistically significant difference in the self-image pressure level and social adaptability score of patients with different ages,marital status,and monthly income.However,there were significant differences in social adaptability among patients with different education levels and employment statuses.The correlation analysis results revealed a significant correlation between the self-image pressure level and social adaptability score before and after surgery.Multiple factors analysis results showed that the degree of concern caused by appearance in selfimage pressure,the degree of possible behavioral intervention,the related distress caused by body image,and the influence of body image on social life influenced the social adaptability of autologous fat breast augmentation patients.CONCLUSION The self-image pressure on autologous fat breast augmentation patients is inversely proportional to their social adaptability.

Investigation of the level spectra of nuclei in the northeast region of doubly magic^(40)Ca with intruder orbit g_(9/2)

This study utilizes large-scale shell model calculations with the extended pairing and multipole–multipole force model(EPQQM)to investigate low-lying states in the nuclei of^(42)Ca,^(42)Sc,and^(42−44)Ti.The model space in this study includes the fp shell as well as the intruder g_(9/2)orbit,which accurately reproduces the positive parity levels observed in the aforementioned nuclei and predicts high energy states with negative parity coupled with the intruder g_(9/2).The study further predicts two different configurations in^(43)Ti at around 6 MeV,specificallyπf_(7/2)^(2)νg_(9/2)andπf_(7/2)g_(9/2)νf_(7/2),both of which involve the intruder orbit g_(9/2).The levels coupled with the intruder g_(9/2)in^(44)Ti are predicted to lie between 7 and 11 MeV.The inclusion of the intruder orbit g_(9/2)is crucial for the exploration of high energy states in the northeast region of the doubly magic nucleus^(40)Ca.

Effects of Multicollinearity on Type I Error of Some Methods of Detecting Heteroscedasticity in Linear Regression Model

Heteroscedasticity and multicollinearity are serious problems when they exist in econometrics data. These problems exist as a result of violating the assumptions of equal variance between the error terms and that of independence between the explanatory variables of the model. With these assumption violations, Ordinary Least Square Estimator (OLS) will not give best linear unbiased, efficient and consistent estimator. In practice, there are several structures of heteroscedasticity and several methods of heteroscedasticity detection. For better estimation result, best heteroscedasticity detection methods must be determined for any structure of heteroscedasticity in the presence of multicollinearity between the explanatory variables of the model. In this paper we examine the effects of multicollinearity on type I error rates of some methods of heteroscedasticity detection in linear regression model in other to determine the best method of heteroscedasticity detection to use when both problems exist in the model. Nine heteroscedasticity detection methods were considered with seven heteroscedasticity structures. Simulation study was done via a Monte Carlo experiment on a multiple linear regression model with 3 explanatory variables. This experiment was conducted 1000 times with linear model parameters of β0 = 4 , β1 = 0.4 , β2= 1.5 and β3 = 3.6. Five (5) levels of mulicollinearity are with seven (7) different sample sizes. The method’s performances were compared with the aids of set confidence interval (C.I.) criterion. Results showed that whenever multicollinearity exists in the model with any forms of heteroscedasticity structures, Breusch-Godfrey (BG) test is the best method to determine the existence of heteroscedasticity at all chosen levels of significance.

基于DEMATEL-AISM的铁路工程建设风险识别影响因素与优化策略研究

铁路工程建设大型化、复杂化和系统化的发展趋势下,潜在的风险因素日益繁多,铁路工程建设高质量和可持续发展之路充满挑战。风险识别作为风险管理的首要环节,是应对和控制铁路工程建设风险的关键,受到项目内外部多方面因素的影响,且现有实践中没有系统的指导,导致风险识别工作易存在疏漏。基于此,通过文献研究和因子分析,提取铁路工程建设风险识别的核心影响因素,运用决策与试验评价实验室和解释结构模型的方法,构建对抗多级递阶结构模型(DEMATEL-AISM),计算铁路工程建设风险识别各影响因素的重要程度及其耦合关系。研究结果表明:铁路工程建设风险识别的效果受到直接层、间接层和根源层3层因素共同作用,其中,危险源监测分析、人员风险意识、风险调查措施、风险应对能力、铁路建设目标、预期风险后果和风险识别技术是影响风险识别结果的关键因素,在铁路工程建设风险管理工作的开展中应重点关注和控制。基于模型结果,分析风险识别影响因素的层级结构及因果关系,并从风险内部控制、项目一体化风险管理体系构建和动态风险预警机制设立3个方面,提出了铁路工程建设风险识别的建议和策略。研究结果有助于提高大型铁路工程建设风险辨识结果的全面性和科学性,对构建铁路工程建设风险识别体系具有一定参考价值和借鉴意义。

水位差法模拟波浪荷载作用下大直径圆筒稳定性离心模型试验研究

某人工岛护岸工程采用大直径圆筒结构,结构直径和高度尺寸较大,工程所处位置波浪条件恶劣。采用水位差法等效模拟波浪荷载,开展波浪荷载作用下大圆筒施工期稳定特性离心模型试验研究,结果表明,在25 a一遇波吸力荷载作用下,筒体位移模式近似平移,侧向位移量约353 mm,筒顶沉降约为187 mm,施工阶段钢圆筒整体稳定;筒壁环向拉应力均值约为90 MPa,处于钢圆筒材料允许应力范围内;筒壁海侧土压力值随水位差增大至峰值后趋于稳定,表明筒体与周围邻近土体之间没有新的相对位移趋势,大直径钢圆筒护岸结构在波浪荷载作用下是稳定安全的。

自主减排、碳关税对中国贸易和福利的影响研究

中国作为《巴黎协定》缔约国之一积极践行自主减排承诺。然而,欧美发达国家/地区无视中国等发展中国家自主减排的贡献,仍以抑制“碳泄露”等为借口征收碳关税,并可能形成碳关税联盟。利用全球能源—环境分析模型在系统评估《巴黎协定》自主减排影响基础上,进一步模拟分析欧盟征收碳关税、美日欧形成碳关税联盟以及低碳技术提升对中国贸易和福利的影响,并探究其影响机制。研究发现:第一,为践行自主减排承诺,中国付出了福利和进出口贸易下降代价,展现了中国作为负责任大国的担当;第二,发达国家/地区征收碳关税将造成中国福利水平的下降,而中国福利水平的下降主要源于中国贸易条件的恶化和贸易量的减少;第三,自主减排和碳关税会深化中国与东盟间的产业合作和经贸往来;第四,中国提升低碳技术可以通过直接和间接两种效应促进国内福利增长,对冲自主减排及碳关税的负面影响。据此提出应加大科研投入提升低碳技术、积极参与国际环境公约与碳排放标准制定、扩大国内碳交易范围并加快碳税立法建设等政策建议。

数据多级保护在反应堆数字孪生体中的应用

针对反应堆数字孪生体建模中常见的树形结构,以经典权限模型为基础,补充和完善该类型客体的访问控制策略,为反应堆数字孪生体建模过程中数据多级保护提供技术解决措施,提升信息的保密性。采用形式化语言描述,对树形结构中各节点的密级设置、授权规则和访问鉴权进行总结并给出定义。非信息安全专业的研究人员在数据建模过程中可方便应用,从而有效提升对孪生体数字资产的保护。

基于结构主题模型的民航管制不安全事件主题识别

为探究民航管制运行不安全事件的发生规律及特点,采用结构主题模型捕捉报告中的词汇共现及层次结构。考虑结构主题的语义连贯性以及排他性等指标,辨识管制运行事件的最优主题数目。选取事件严重度及发生时间等协变量,构建融合多变量的主题分析,挖掘不同类型事件的严重度差异性及在时间维度上的演化趋势。最后,基于航空安全自愿报告系统2018-2022年的4346起管制事件报告进行实证分析。研究结果表明:与管制运行有关的不安全事件可分为管制移交、恶劣天气、人为因素事件、夜航航班、场面滑行、起飞离场、部门协调、雷达间隔、设备故障、进近程序、陆空对话、复杂空域环境、飞行冲突、飞行高度、冲/偏出跑道及跑道侵入15类;飞行区滑行、进近程序、飞行冲突等事件更易产生严重事故;飞行高度有关的不安全事件呈逐年上升趋势。研究结果可为提升管制运行安全风险水平提供理论支持,并为管理人员针对性施策提供参考。

县域城镇化背景下关中平原城市群近郊农民外出行为决策机理研究

研究县域城镇化背景下农民外出行为决策机理,是有效引导农业人口就地就近转移、缓解“大城市病”、促进城乡融合发展的重要基础工作。本文基于城乡人口流动视角,依据推拉理论和计划行为理论构建农民外出行为决策机理模型,采集关中平原城市群近郊农村调研问卷362份,运用结构方程模型实证了该地区农民外出行为决策机理。结果表明:1)感知推力、感知拉力、感知核力通过影响农民外出行为态度及意愿间接作用于外出实际行为。其中,感知推力和感知拉力为正向影响,感知核力为负向影响。2)农民的感知个人能力和感知家庭能力在外出行为意愿与外出实际行为之间具有显著的调节作用,且感知个人能力的调节作用更强。最后,基于决策机理探讨了县域城镇化政策含义并提出了提升村容村貌减弱农村推力作用、盘活闲置资产巩固农村核力优势、丰富乡镇经济业态增强乡镇拉力作用、多途径多渠道提升农民县城生活品质等对策建议。

层冰作用下直立圆柱结构冰载荷研究

层冰是冰区海工结构作业时遭遇的主要冰况之一,直立结构是海工结构的常见构型,因此,开展层冰作用下直立结构冰载荷研究对海工结构抗冰强化设计和安全评估具有重要意义。本文首先对层冰与直立结构作用过程进行概括分析。然后开展直立圆柱结构冰载荷的机理性试验,研究层冰的失效行为以及结构冰载荷的特征。最后基于黏聚单元模型和海冰软化本构开发层冰与结构作用模拟的数值仿真模型,对层冰的裂纹扩展和破碎过程进行模拟,同时利用试验数据对数值仿真模型的正确性进行验证。本研究工作可为结构冰载荷的数值和试验研究奠定重要基础,为冰区海工结构的设计建造提供技术参考。

基于粘聚力单元的平整冰与海洋桩柱结构相互作用机理研究

平整冰与海洋桩柱结构的相互作用问题十分复杂,往往涉及到海冰的破碎、失效和堆积等现象。平整冰破坏问题本质上是一个材料脆性破坏的问题,然而传统有限元方法的单元失效机制在处理该问题时有着很大的局限性,不能合理反映平整冰破碎后碎冰的变形和运动状态。因此,有必要发展现有仿真技术,建立合理的模型化方法来解决平整冰破坏相关关键问题。本文通过自定义海冰材料本构模拟海冰材料力学特性,并通过粘聚力单元模拟平整冰破坏时裂纹的产生和扩展,通过开展海洋桩柱结构与平整冰相互作用的仿真分析,分析平整冰在受桩柱作用时的破坏失效模式及两者的相互作用载荷,并与相关模型试验比较验证本文所提出方法的可靠性。研究表明,本文所采用的方法能够有效模拟平整冰在受桩柱作用时的挤压和弯曲破坏,同时能够较为准确地预报冰载荷。研究成果对于海洋桩柱结构冰载荷的预报和结构的设计具有重要的参考意义。

古建筑木结构透榫节点地震损伤演化模型研究

为定量评估古建筑木结构透榫节点的地震损伤程度与地震损伤演化过程,对Kratzig地震损伤模型进行了改进。分别基于刁波地震损伤模型、Kratzig地震损伤模型以及改进的Kratzig地震损伤模型对3组透榫节点进行了地震损伤分析,研究了3种模型的适用性。为了对实际工程中的透榫节点松动进行地震损伤评估,基于改进的Kratzig地震损伤模型,考虑了节点松动对改进的Kratzig地震损伤模型的影响。结果表明:改进的Kratzig地震损伤模型在描述透榫节点地震损伤中表征效果最好,能够克服地震损伤模型与Kratzig地震损伤模型的不足;随着松动程度的增大,透榫节点损伤指数增长减缓,最终破坏时损伤指数减小。最后根据国内抗震设防规范,结合古建筑木结构地震损伤评估,提出了透榫节点性能水准分类及每个阶段的加固建议。

基于伪触发词的并行预测篇章级事件抽取方法

篇章级事件抽取一般将事件抽取任务分为候选实体识别、事件检测和论元识别3个子任务,然后采用级联的方式依次进行,这样的方式会造成误差传递;另外,现有的大多数模型在解码事件时,对事件数量的预测隐含在解码过程中,且只能按照预定义的事件顺序及预定义的角色顺序预测事件论元,使得先抽取的事件并没有考虑到后面抽取的事件。针对以上问题提出一种多任务联合的并行预测事件抽取框架。首先,使用预训练语言模型作为文档句子的编码器,检测文档中存在的事件类型,并使用结构化自注意力机制获取伪触发词特征,预测每种事件类型的事件数量;然后将伪触发词特征与候选论元特征进行交互,并行预测每个事件对应的事件论元,在大幅缩减模型训练时间的同时获得与基线模型相比更好的性能。最终事件抽取结果F1值为78%,事件类型检测子任务F1值为98.7%,事件数量预测子任务F1值为90.1%,实体识别子任务F1值为90.3%。

SD-pair structure in the pair approximation of the nuclear shell model

In this paper we study the structure coeficients of collective pairs with spin zero and spin two (SD) in a number of configurations by a few realistic nuclei. We investigate the robustness of these structure coeffcients with respect to different configurations and the evolution of SD-pair structure coeffcients with valence nucleon number.

中学生物理概念理解水平的性别差异:影响因素及作用机制

大量研究表明,男生在物理学科能力和学习动机方面的表现显著优于女生。为探究外界评价和物理学习动机对学生物理概念理解的作用机制,本文选取252名高中生为样本,用结构方程模型分析性别差异的形成机制。该模型显示物理身份认同能够显著正向预测学生物理概念理解水平,而学习兴趣和自我效能感对其没有显著影响。外界评价是导致男女生物理身份认同存在显著差异的重要原因。女生感知到来自他人的认可度低,破坏了其物理身份认同的形成发展过程,从而进一步影响了女生在物理学习中的表现。