Optimized numerical density functional theory calculation of rotationally symmetric jellium model systems

In real space density functional theory calculations,the effective potential depends on the electron density,requiring self-consistent iterations,and numerous integrals at each step,making the process time-consuming.In our research,we propose an optimization method to expedite density functional theory(DFT)calculations for systems with large aspect ratios,such as metallic nanorods,nanowires,or scanning tunneling microscope tips.This method focuses on employing basis set to expand the electron density,Coulomb potential,and exchange-correlation potential.By precomputing integrals and caching redundant results,this expansion streamlines the integration process,significantly accelerating DFT computations.As a case study,we have applied this optimization to metallic nanorod systems of various radii and lengths,obtaining corresponding ground-state electron densities and potentials.

On the Proof of the Contradiction of Set Theory

The article is devoted to proving the inconsistency of set theory arising from the existence of strange trees. All steps of the proof rely on common informal set-theoretic reasoning, but they take into account the prohibitions that were introduced into axiomatic set theories in order to overcome the difficulties encountered by the naive Cantor set theory. Therefore, in fact, the article is about proving the inconsistency of existing axiomatic set theories, in particular, the ZFC theory.

Proof of Concept for a Twin Prime Number Universe Using Set Theory

The Fine Structure Constant (eFSC) Model attempts to give a classical definition to a magical number that underlies much of quantum physics. The Fine Structure Constant (α) value equal to 137.03599206 represents a dimensionless constant that characterizes the strength of the electromagnetic (EM) interaction between subatomic charged particles. Python-generated property counts for the twin prime force F{139/137} show that the adjusted ratio gives a value of α = 137.036. This implies a mathematical framework underlying this constant is based on twin prime numbers and set theory. This study attempts to demonstrate a proof of concept that a hierarchy of fractional twin prime (αII) forces replicates the quantum nature of the universe and is aligned with the Standard Model of Particle Physics. An expanded eFSC Model demonstrates that twin prime forces and their property sets are mathematically viable substitutes for nuclear reactions, as demonstrated for the Beta-minus decay of neutrons into protons. Most significantly, the positive and negative prime numbers define these nuclear reactants and products as positive or negatively charged ions. Furthermore, the eFSC Model provides new insights regarding the hierarchy of EM forces underlying the quantum nature of the universe.

Globalization Under the Spells of Breakdowns in Supply Chains, Regime Change, Regime Formation, and Alliance Restructuring: How Much Is Left for Public Goods?

In a paper conceived about five years ago(“Globalization and Public Goods:Too Big to Tackle?”)roughly a dozen factors were linked to explain important causal paths from globalization to the potential output of public goods.The Russian invasion of Ukraine,the corona epidemic,and the increased hegemonic rivalry between China and the U.S.interrupted or even destroyed many of the linkages between globalization and potential public good production.About five important detrimental paths involved in the meantime.In the present article we aim at linking what is left from the previous level of globalization or emerging to form a new and simplified causal model for likely linkages between truncated or(re-)emerging globalization,and the deadly needed output of public goods.These linkages refer to rules of climate control,go to trade linkages and arbitrary tariffs and trade interventions.Regime change,regime formation,and alliance restructuring address aspects of domestic rule and international stability.Selectorate theory,regime type,and exit options for political elites provide key explanatory factors in explaining globalization and public goods productions,or their decay.Where possible we use some data and transformation experiences corroborating our arguments.In other instances need for further empirical macro research will become clear.

Two kinds of average approximation accuracy

Rough set theory places great importance on approximation accuracy,which is used to gauge how well a rough set model describes a target concept.However,traditional approximation accuracy has limitations since it varies with changes in the target concept and cannot evaluate the overall descriptive ability of a rough set model.To overcome this,two types of average approximation accuracy that objectively assess a rough set model’s ability to approximate all information granules is proposed.The first is the relative average approximation accuracy,which is based on all sets in the universe and has several basic properties.The second is the absolute average approximation accuracy,which is based on undefinable sets and has yielded significant conclusions.We also explore the relationship between these two types of average approximation accuracy.Finally,the average approximation accuracy has practical applications in addressing missing attribute values in incomplete information tables.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Runoff change in the Yellow River Basin of China from 1960 to 2020 and its driving factors

Analysing runoff changes and how these are affected by climate change and human activities is deemed crucial to elucidate the ecological and hydrological response mechanisms of rivers.The Indicators of Hydrologic Alteration and the Range of Variability Approach(IHA-RVA)method,as well as the ecological indicator method,were employed to quantitatively assess the degree of hydrologic change and ecological response processes in the Yellow River Basin from 1960 to 2020.Using Budyko's water heat coupling balance theory,the relative contributions of various driving factors(such as precipitation,potential evapotranspiration,and underlying surface)to runoff changes in the Yellow River Basin were quantitatively evaluated.The results show that the annual average runoff and precipitation in the Yellow River Basin had a downwards trend,whereas the potential evapotranspiration exhibited an upwards trend from 1960 to 2020.In approximately 1985,it was reported that the hydrological regime of the main stream underwent an abrupt change.The degree of hydrological change was observed to gradually increase from upstream to downstream,with a range of 34.00%-54.00%,all of which are moderate changes.However,significant differences have been noted among different ecological indicators,with a fluctuation index of 90.00%at the outlet of downstream hydrological stations,reaching a high level of change.After the mutation,the biodiversity index of flow in the middle and lower reaches of the Yellow River was generally lower than that in the base period.The research results also indicate that the driving factor for runoff changes in the upper reach of the Yellow River Basin is mainly precipitation,with a contribution rate of 39.31%-54.70%.Moreover,the driving factor for runoff changes in the middle and lower reaches is mainly human activities,having a contribution rate of 63.70%-84.37%.These results can serve as a basis to strengthen the protection and restoration efforts in the Yellow River Basin and further promote the rational development and use of water resources in the Yellow River.

Se situer dans la continuitéd’un dialogue interdisciplinaire de recherche:entre transmission et renégociation du《commun》 Aligning in the Continuity of an Interdisciplinary Research Dialogue: Between Transmission and Renegotiation of the ‘Common’

This paper aims to highlight the challenges of continuing and resuming interdisciplinary dialogue between physicians and psychologists in thefield of research,after the institutionalization and establishment of this collaboration at the institutional level.By comparing two research frameworks that follow each other in the same researchfield,we will examine the negotiation process of interdisciplinary dialogue and the ways in which it manifests in the researchfield,mediated by the interaction between healthcare professionals and researchers.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave.The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method.It also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow implication.Thismethodology can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic zone.The Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara differentiability.According to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in detail.The illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are known.Based on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.

The Application of Goal-Setting Theory in the Second Classroom Teaching Activities of College English

Interest is the precondition and motivation for people's accomplishment.However,due to the exam-oriented system,millions of parents and teachers neglect the interests of children,and our children nearly forget their interests or hobbies.Based on different interests of children,the thesis analyzes how to apply the goal-setting theory in the second classroom teaching activities of College English,using the example of Lushan College of Guangxi University of Technology.

About the Strange Tree Paradox and Possible Inconsistency of Set Theory

The existence of “strange trees” is proven and their paradoxical nature is discussed, due to which set theory is suspected of being contradictory. All proofs rely on informal set-theoretic reasoning, but without using elements that were prohibited in axiomatic set theories in order to overcome the difficulties encountered by Cantor’s naive set theory. Therefore, in fact, the article deals with the possible inconsistency of existing axiomatic set theories, in particular, the ZFC theory. Strange trees appear when uncountable cardinals appear.

Organizational Psychology Revisited: Recent Applications of Goal-Setting Theory

Purpose:Goal Setting Theory(GST)created by Edwin Locke and Gary Latham has proven to be an incredibly versatile theory.Its widespread utilization has proven it to be a valuable theory to further explore and understand.The purpose of this paper is to examine current approaches to and practices of GST.Methodology:This systematic literature review is based on 12 recent articles using GST and examining their collective findings.The articles were a mix of theory description,quantitative experiments,empirical experiments,and literature review.Findings:Most of the reviewed literature agreed that further and more defined research would be greatly beneficial for future applications of this theory.Given the broad nature of this theory,a more defined approach would likely prove useful for future utilization.Value:Exploring the multitude of ways this theory has already been applied gives an understanding of shortcomings as well as successes.Reviewing the current available literature allows GST to be utilized in a more precise way in the future.

结合未知类特征生成与分类得分修正的SAR目标开集识别方法

现有合成孔径雷达(SAR)目标识别方法大多局限于闭集假定,即认为训练模板库内训练目标类别包含全部待测目标类别,不适用于库内已知类和库外未知新类目标共存的真实开放识别环境。针对训练模板库目标类别非完备情况下的SAR目标识别问题,该文提出一种结合未知类特征生成与分类得分修正的SAR目标开集识别方法。该方法在利用已知类学习原型网络保证已知类识别精度的基础上结合对潜在未知类特征分布的先验认知,生成未知类特征更新网络,进一步保证特征空间中已知类、未知类特征的鉴别性。原型网络更新完成后,所提方法挑选各已知类边界特征,并计算边界特征到各自类原型的距离(极大距离),通过极值理论对各已知类极大距离进行概率拟合确定了各已知类最大分布区域。测试阶段在度量待测样本特征与各已知类原型距离预测闭集分类得分的基础上,计算了各距离在对应已知类极大距离分布上的概率,并修正闭集分类得分,实现了拒判概率的自动确定。基于MSTAR实测数据集的实验结果表明,所提方法能够有效表征真实未知类特征分布并提升网络特征空间已知类与未知类特征的鉴别性,可同时实现对库内已知类目标的准确识别和对库外未知类新目标的准确拒判。

制造企业智能化转型绩效影响因素的组态效应——基于“动机-能力-机会”(AMO)理论分析框架

制造企业智能化转型是多种要素协同作用的结果,而如何提升转型绩效是当前中国制造企业面临的主要难题。但学界针对此议题的深入研究尚较为缺乏。对此,首先对制造企业智能化转型概念作出定义并分析其内涵要素;其次,鉴于组织、团队或个体的绩效水平会受到其能力(ability)、动机(motivation)和机会(opportunity)等多方面因素的影响,基于“动机-能力-机会”(AMO)理论框架构建制造企业智能化转型绩效影响因素的组态模型;最后,采用面向全国制造企业的103份有效调查问卷数据,并结合典型案例,运用模糊集定性比较分析方法(fsQCA)分析企业转型能力(企业动态能力、企业知识禀赋)、转型动机(内在转型需求、外部竞争压力)以及转型机会(政府政策支持、数字基础设施)对于样本企业智能化转型绩效的组态效应。结果表明:能力、动机和机会均无法单独构成制造企业高智能化转型绩效的必要条件;存在8种会导致企业高智能化转型绩效的条件组态并可归纳为能力主导机会支持型、动机主导能力支持型、动机主导机会支持型、机会主导能力支持型和能力、动机、机会兼备型五大组态类型;有1种条件组态会导致企业非高智能化转型绩效,可归纳为能力、动机、机会兼不具备型。由此得到启示:制造企业在向智能制造转型升级的过程中须重视对自身能力、动机和机会三者情况进行综合性考量,结合实际选择合理的转型升级路径。

工程起重伤害事故影响因素分析与组态效应研究:基于扎根理论和fsQCA方法

起重伤害事故是影响施工安全的主要因素之一,研究其复杂性成因有利于建筑行业的可持续管理。以中国的94份工程起重伤害事故作为有效样本,运用扎根理论识别与提取起重伤害事故的致因因素,得到了207个初始概念、33个开放性编码、6个主轴编码。在此基础上,构建起重伤害事故影响因素模型,并将扎根理论与模糊集定性比较分析方法的优势互补后进行结合,揭示了工程施工现场起重伤害事故致因因素的组态效应及复杂交互机理。研究发现:起重伤害事故的致因因素可以分为人机状态、现场环境与监管质量3个层次,包括作业人员的不安全行为和作业现场的不安全环境等六大类别。单个因素无法单独构成起重伤害事故的必要条件,有三类条件组态构成起重伤害事故的驱动路径。施工现场起重伤害事故是多因素的协同作用,因素的交互组合以“殊途同归”的方式加大了起重事故的伤害程度。

科教融合背景下大学生创新能力培养的影响因素与作用路径研究——基于经典扎根理论与fsQCA的混合式方法

科教融合对于激发大学生的好奇心和求知欲、培养大学生的创新能力和科学精神具有重要意义,然而当前学术界对于科教融合背景下大学生创新能力培养的研究尚不深入。基于科教融合背景,运用经典扎根理论深入探讨大学生创新能力培养的影响因素,进而运用模糊集定性比较分析(fsQCA)的方法,揭示大学生创新能力培养的形成路径与作用机理。研究结果表明:第一,科研志趣、自我效能感、融合教学能力、研究性学习意愿与多元学业评价机制均为影响大学生创新能力的重要因素,但单个影响因素不是培养大学生创新能力的必要条件;第二,科教融合背景下大学生创新能力的培养,存在教学—研究双驱型、内外协同型、科研主动型和评价激励型四条路径。研究结论对科教融合背景下大学生创新能力的培养具有一定的指导意义。

Bifurcation and dynamic response analysis of rotating blade excited by upstream vortices

A reduced model is proposed and analyzed for the simulation of vortexinduced vibrations （VIVs） for turbine blades. A rotating blade is modelled as a uniform cantilever beam, while a van der Pol oscillator is used to represent the time-varying characteristics of the vortex shedding, which interacts with the equations of motion for the blade to simulate the fluid-structure interaction. The action for the structural motion on the fluid is considered as a linear inertia coupling. The nonlinear characteristics for the dynamic responses are investigated with the multiple scale method, and the modulation equations are derived. The transition set consisting of the bifurcation set and the hystere- sis set is constructed by the singularity theory and the effects of the system parameters, such as the van der Pol damping. The coupling parameter on the equilibrium solutions is analyzed. The frequency-response curves are obtained, and the stabilities are determined by the Routh-Hurwitz criterion. The phenomena including the saddle-node and Hopf bifurcations are found to occur under certain parameter values. A direct numerical method is used to analyze the dynamic characteristics for the original system and verify the va- lidity of the multiple scale method. The results indicate that the new coupled model is useful in explaining the rich dynamic response characteristics such as possible bifurcation phenomena in the VIVs.

Impacts of future climate change(2030-2059)on debris flow hazard:A case study in the Upper Minjiang River basin,China

An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil,vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation(2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.

Mathematical Morphology View of Topological Rough Sets and Its Applications

This article focuses on the relationship between mathematical morphology operations and rough sets,mainly based on the context of image retrieval and the basic image correspondence problem.Mathematical morphological procedures and set approximations in rough set theory have some clear parallels.Numerous initiatives have been made to connect rough sets with mathematical morphology.Numerous significant publications have been written in this field.Others attempt to show a direct connection between mathematical morphology and rough sets through relations,a pair of dual operations,and neighborhood systems.Rough sets are used to suggest a strategy to approximatemathematicalmorphology within the general paradigm of soft computing.A single framework is defined using a different technique that incorporates the key ideas of both rough sets and mathematical morphology.This paper examines rough set theory from the viewpoint of mathematical morphology to derive rough forms of themorphological structures of dilation,erosion,opening,and closing.These newly defined structures are applied to develop algorithm for the differential analysis of chest X-ray images from a COVID-19 patient with acute pneumonia and a health subject.The algorithm and rough morphological operations show promise for the delineation of lung occlusion in COVID-19 patients from chest X-rays.The foundations of mathematical morphology are covered in this article.After that,rough set theory ideas are taken into account,and their connections are examined.Finally,a suggested image retrieval application of the concepts from these two fields is provided.