Four-Electron Systems in the Impurity Hubbard Model. Second Triplet State. Spectra of the System in the ν-Dimensional Lattice Zν

We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.

From the Hubble Constant to the Black Hole Model. Universe Expansion with Matter Creation and a New Perspective on Dark Energy Observations

Comparison of the Hubble parameter with cosmological quantities strongly supports the black hole model for the description of the Universe evolution. Such evolution requires matter creation and has implications for what is currently referred to as “dark energy” and the “cosmological constant”.

Hypersphere World-Universe Model. Tribute to Classical Physics

This manuscript summarizes the results of Classical Physics before Quantum Mechanics and Hypotheses proposed by classical physicists from the 17th until the beginning of 21st century. We then proceed to unify these results into a single coherent picture in frames of the developed Hypersphere World-Universe Model (WUM). The Model proposes 5 types of Dark Matter particles and predicts their masses;models the origin, evolution, and structure of the World and Macroobjects;provides a mathematical framework that ties together a number of Fundamental constants and allows for direct calculation of their values.

5D World-Universe Model. Multicomponent Dark Matter

5D World-Universe Model (WUM) is based on the decisive role of the Medium of the World com-posed of massive particles: protons, electrons, photons, neutrinos, and Dark Matter Particles (DMP). The model forecasts the masses of DMP, discusses the possibility of all macroobject cores consisting of DMP (galaxy clusters, galaxies, star clusters, extrasolar systems, and planets), and explains the diffuse cosmic gamma-ray background radiation as the sum of contributions of multicomponent dark matter annihilation. The signatures of DMP annihilation with expected masses of 1.3 TeV, 9.6 GeV, 70 MeV, 340 keV, and 3.7 keV, are found in spectra of the diffuse gamma-ray background and the emission of various macroobjects in the World. The correlation between different emission lines in spectra of macroobjects is connected to their structure, which depends on the composition of the cores and surrounding shells made up of DMP. Consequently, the diversity of Very High Energy (VHE) gamma-ray sources in the World has a clear explanation.

The integration of nitrogen dynamics into a land surface model. Part 1: model description and site-scale validation

Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes.However,nutrient cycling is not taken into account in most land surface models for climate change.In this study,a nitrogen model,based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem,was incorporated into the Atmosphere–Vegetation Interaction Model(AVIM)to simulate the carbon cycle under nitrogen limitation.This new model,AVIM-CN,was evaluated against site-scale eddy covariance–based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset.Results showed that the annual mean gross primary production simulated by AVIM-CN(0.7073 gC m^-2 d^-1)was in better agreement with the corresponding flux data(0.5407 gC m^-2 d^-1)than the original AVIM(1.1403 gC m^-2 d^-1)at Damxung station.Similarly,ecosystem respiration was also down-regulated,from 1.7695 gC m^-2 d^-1 to 1.0572 gC m^-2 d^-1,after the nitrogen processes were introduced,and the latter was closer to the observed vales(0.8034 gC m^-2 d^-1).Overall,the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics.A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.

Structure of Essential Spectrum and Discrete Spectra of the Energy Operator of Five-Electron Systems in the Hubbard Model. Third and Fourth Doublet States

We consider a five-electron system in the Hubbard model with a coupling between nearest-neighbors. The structure of essential spectrum and discrete spectrum of the systems in the third and fourth doublet states in a v-dimensional lattice is investigated. We prove that the essential spectrum of the system in a third doublet state consists is the union of at most four segments, and discrete spectrum of the system is empty. We show that the essential spectrum of the system in a fourth doublet state consists of the union of at most seven segments, and discrete spectrum of the system consists of no more than one point.

5D World-Universe Model. Gravitation

5D World-Universe Model is based on the decisive role of the Medium of the World composed of massive particles: protons, electrons, photons, neutrinos, and dark matter particles. In this manuscript we discuss different aspects of the gravitation: measured values of the Newtonian parameter of Gravitation and different Gravitational effects (gravitational lensing, cosmological redshift, gravitational deflection of light and gravitational refraction, proposed in the present paper). We show inter-connectivity of all cosmological parameters and provide a mathematical framework that allows direct calculation of them based on the value of the gravitational parameter. We analyze the difference between Electromagnetism and Gravitoelectromagnetism and make a conclusion about the mandatory existence of the Medium of the World. This paper aligns the World-Universe Model with the Le Sage’s theory of gravitation and makes a deduction on Gravity, Space and Time be emergent phenomena.

5D World-Universe Model. Neutrinos. The World

In this manuscript we discuss mass-varying neutrinos and propose their energy density to exceed that of baryonic and dark matter. We introduce cosmic Large Grains whose mass is about Planck mass, and their temperature is around 29 K. Large Grains are in fact Bose-Einstein condensates of proposed dineutrinos, and are responsible for the cosmic Far-Infrared Background (FIRB) radiation. The distribution of the energy density of all components of the World (protons, electrons, photons, neutrinos, and dark matter particles) is considered. We present an overview of the World- Universe Model (WUM) and pay particular attention to the self-consistent set of time-varying values of basic parameters of the World: the age and critical energy density;Newtonian parameter of gravitation and Hubble’s parameter;temperatures of the cosmic Microwave Background radiation and the peak of the cosmic FIRB radiation;Fermi coupling parameter and coupling parameters of the proposed Super-Weak and Extremely-Weak interactions. Additionally, WUM forecasts the masses of dark matter particles, axions, and neutrinos;proposes two fundamental parameters of the World: fine-structure constant α and the quantity Q which is the dimensionless value of the fifth coordinate, and three fundamental physical units: basic unit of momentum, energy density, and energy flux density. WUM suggests that all time-dependent parameters of the World are inter- connected and in fact dependent on Q. We recommend adding the quantity Q to the list of the CODATA-recommended values.

Spectra of the Energy Operator of Four-Electron Systems in the Impurity Hubbard Model. Triplet State

We consider the energy operator of four-electron systems in an impurity Hubbard model and investigated the structure of essential spectra and discrete spectrum of the system in the first triplet state in a one-dimensional lattice. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model. The investigations show that there are such cases: 1) the essential spectrum of the system consists of the union of no more than eight segments, and the discrete spectrum of the system consists of no more than three eigenvalues;2) the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues;3) the essential spectrum of the system consists of the union of no more than three segments, and the discrete spectrum of the system is the empty set. Consequently, the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.

Structure of Essential Spectra and Discrete Spectrum of the Energy Operator of Six-Electron Systems in the Hubbard Model. First Quintet and First Singlet States

We consider the energy operator of six-electron systems in the Hubbard model and investigate the structure of essential spectra and discrete spectrum of the system in the first quintet and first singlet states in the v-dimensional lattice.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

ChatModeler:基于大语言模型的人机协作迭代式需求获取和建模方法

需求获取和建模是需求工程中的关键步骤,影响后续系统设计与实现.传统的需求获取和建模方法通常由需求提供者、需求分析师等多类干系人共同协作、反复迭代完成,需要耗费大量的人力.如何减轻需求提供者与需求分析师的负担、提高获取和建模的效率有着重要意义.现有工作中有的使用知识库来提供更多知识,以辅助获取或者建模,有的利用自然语言处理等技术对获取或者建模过程进行自动化,但是它们并没有减轻需求提供者的负担.利用大语言模型(large language models,LLMs)的生成能力,提供了一种人机协作的迭代式需求获取和建模框架ChatModeler.具体来说,根据真实世界中需求团队的分工及协作关系,将部分需求提供者、需求分析师等角色的工作由大语言模型承担,而需求提供者只需要进行确认.为大语言模型扮演的各种角色进行了提示词设计,该提示词会随需求的元模型而变化.ChatModeler在7个需求案例上与3种需求模型的自动建模方法进行了14组对比实验,证明了ChatModeler在降低需求提供者的负担和生成高质量需求模型2个方面上的优越性.

Effects of mesenchymal stem cell on dopaminergic neurons,motor and memory functions in animal models of Parkinson's disease:a systematic review and meta-analysis

Parkinson’s disease is chara cterized by the loss of dopaminergic neurons in the substantia nigra pars com pacta,and although restoring striatal dopamine levels may improve symptoms,no treatment can cure or reve rse the disease itself.Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease.Mesenchymal stem cells are considered a promising option due to fewer ethical concerns,a lower risk of immune rejection,and a lower risk of teratogenicity.We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function,memory,and preservation of dopamine rgic neurons in a Parkinson’s disease animal model.We searched bibliographic databases(PubMed/MEDLINE,Embase,CENTRAL,Scopus,and Web of Science)to identify articles and included only pee r-reviewed in vivo interve ntional animal studies published in any language through J une 28,2023.The study utilized the random-effect model to estimate the 95%confidence intervals(CI)of the standard mean differences(SMD)between the treatment and control groups.We use the systematic review center for laboratory animal expe rimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment.A total of 33studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis.Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test.Among the stem cell types,the bone marrow MSCs with neurotrophic factor group showed la rgest effect size(SMD[95%CI]=-6.21[-9.50 to-2.93],P=0.0001,I^(2)=0.0%).The stem cell treatment group had significantly more tyrosine hydroxylase positive dopamine rgic neurons in the striatum([95%CI]=1.04[0.59 to 1.49],P=0.0001,I^(2)=65.1%)and substantia nigra(SMD[95%CI]=1.38[0.89 to 1.87],P=0.0001,I^(2)=75.3%),indicating a protective effect on dopaminergic neurons.Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route(SMD[95%CI]=-2.59[-3.25 to-1.94],P=0.0001,I^(2)=74.4%).The memory test showed significant improvement only in the intravenous route(SMD[95%CI]=4.80[1.84 to 7.76],P=0.027,I^(2)=79.6%).Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson’s disease.Further research is required to determine the optimal stem cell types,modifications,transplanted cell numbe rs,and delivery methods for these protocols.

Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models

Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Genetically modified non-human primate models for research on neurodegenerative diseases

Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(HD),and amyotrophic lateral sclerosis(ALS).Currently,there are no therapies available that can delay,stop,or reverse the pathological progression of NDs in clinical settings.As the population ages,NDs are imposing a huge burden on public health systems and affected families.Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments.While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms,the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap.Old World nonhuman primates(NHPs),such as rhesus,cynomolgus,and vervet monkeys,are phylogenetically,physiologically,biochemically,and behaviorally most relevant to humans.This is particularly evident in the similarity of the structure and function of their central nervous systems,rendering such species uniquely valuable for neuroscience research.Recently,the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms.This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained,as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).