An Exploration of the Three Dimensions and Epochal Strengths of Building a Human Community With a Shared Future

The idea of a human community with a shared future was proposed by the Communist Party of China(CPC)Central Committee with Comrade Xi Jinping at its core for the future development of human beings to face up to the most important question in today's world:“What is happening to the world and what should we do?”It profoundly answers the question of the world,history,and the times.The theory of a human community with a shared future is an innovative theory with a multidimensional formation logic that guides humanity toward continually seeking common interests and values.This paper dives into the profound motivations behind building a human community with a shared future from historical,cultural,and practical dimensions and analyzes its epochal value from both domestic and international perspectives.This not only helps exert China's role in the international community,contributing Chinese strength to the construction of a peaceful,stable,and prosperous human society,but also enhances the influence of the idea of a human community with a shared future in the international community,accelerating the building of a human community with a shared future that considers the legitimate concerns of all countries,and aiding in solving the crises facing the world.

Rectangular tunnel heading stability in three dimensions and its predictive machine learning models

Tunnel heading stability in two dimensions(2D)has been extensively investigated by numerous scholars in the past decade.One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization.Nevertheless,it is possible to study the stability of tunnels in three dimensions(3D)with a rectangular shape using finite element limit analysis(FELA)and a nonlinear programming technique.This paper employs 3D FELA to generate rigorous solutions for stability numbers,failure mechanisms,and safety factors for rectangular-shaped tunnels.To further explore the usefulness of the produced results,multivariate adaptive regression spline(MARS)is used for machine learning of big dataset and development of design equations for practical design applications.The study should be of great benefit to tunnel design practices using the developed equations provided in the paper.

Redefining gaming addictive behavior:influence of media,psychological dimensions and clinical implications

This review critically examines gaming addiction within the contexts of media psychology and addiction theory.It outlines a continuum of gaming behavior,from casual play to addiction,characterized by loss of control,prioritizing gaming over other activities,and negative life consequences.The inclusion of gaming disorder in International Classification of Disease 11 and its provisional status in Diagnostic and Statistical Manual of Mental Disorder 5 highlight growing clinical and societal recognition.The review explores neural correlates of gaming addiction,such as activation in reward-related brain regions,drawing parallels with substance addiction.It highlights how media and marketing promote gaming behaviors potentially leading to addiction,raising ethical concerns about game design and advertising.The review systematically analyzes the negative physical,mental,social,and occupational impacts of gaming addiction.It advocates for a balanced approach emphasizing awareness,therapeutic interventions,and responsible media practices,while also proposing areas for future research and policy development to mitigate the risks of excessive gaming.

The Historical Position and Value Dimensions of Human Rights Civilization

Human beings are the mainstay and the ultimate goal of civilization.The history of human civilization is a continuous struggle to realize the respect,liberation,protection,and development of humanity.Human rights are an achievement of humanity and a symbol of progress,and the human rights civilization is an important component of human civilization.Understanding and interpreting human rights from the perspective of human rights civilization means that human rights are not only a concept or an idea but also a grand historical and long-term social practice.Up to now,the development of human rights civilization has roughly experienced four awakening eras:initialization,revolution,popularization,and globalization.In terms of its value dimensions,it has the characteristics of progressiveness,diversity,commonality,inclusiveness,indivisibility,openness,and so on.The historical position of human rights civilization and the development of its value dimensions have shown to the world that human rights are the common wealth of humanity,and human rights belong to all mankind;human rights are historical,concrete,and developmental;the concept of human rights is constantly evolving,and its connotations and categories are constantly expanding;achieving the free and well-rounded development of every person is the highest value realm of human rights civilization.The Chinese modernization endows Chinese civilization with modern strength and opens up new horizons for human rights civilization.The new pattern of human rights civilization to be created by Chinese modernization not only possesses the common characteristics of human rights civilization but also enjoys Chinese characteristics based on its own national conditions,enriching and developing the diversity of human rights civilization for all mankind.

Cosmological Model in Four Time and Four Space Dimensions

We develop a cosmological model in a physical background scenario of four time and four space dimensions ((4+4)-dimensions or (4+4)-universe). We show that in this framework the (1+3)-universe is deeply connected with the (3+1)-universe. We argue that this means that in the (4+4)-universe there exists a duality relation between the (1+3)-universe and the (3+1)-universe.

Suppression of stimulated Raman scattering by angularly incoherent light, towards a laser system of incoherence in all dimensions of time, space, and angle

Laser–plasma instability(LPI)is one of the main obstacles to achieving predictable and reproducible fusion at high gain through laser-driven inertial confinement fusion(ICF).In this paper,for the first time,we show analytically and confirm with three-dimensional particle-incell simulations that angular incoherence provides suppression of the instability growth rate that is additional to and much stronger than that provided by the well-known temporal and spatial incoherence usually used in ICF studies.For the model used in our calculations,the maximum field ratio between the stimulated Raman scattering and the driving pulses drops from 0.2 for a Laguerre–Gaussian pulse with a single nonzero topological charge to 0.05 for a super light spring with an angular momentum spread and random relative phases.In particular,angular incoherence does not introduce extra undesirable hot electrons.This provides a novel method for suppressing LPI by using light with an angular momentum spread and paves the way towards a low-LPI laser system for inertial fusion energy with a super light spring of incoherence in all dimensions of time,space,and angle,and may open the door to the use of longer-wavelength lasers for inertial fusion energy.

Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

In traditional finite-temperature Kohn–Sham density functional theory(KSDFT),the partial occupation of a large number of high-energy KS eigenstates restricts the use of first-principles molecular dynamics methods at extremely high temperatures.However,stochastic density functional theory(SDFT)can overcome this limitation.Recently,SDFT and the related mixed stochastic–deterministic density functional theory,based on a plane-wave basis set,have been implemented in the first-principles electronic structure software ABACUS[Q.Liu and M.Chen,Phys.Rev.B 106,125132(2022)].In this study,we combine SDFT with the Born–Oppenheimer molecular dynamics method to investigate systems with temperatures ranging from a few tens of eV to 1000 eV.Importantly,we train machine-learning-based interatomic models using the SDFT data and employ these deep potential models to simulate large-scale systems with long trajectories.Subsequently,we compute and analyze the structural properties,dynamic properties,and transport coefficients of warm dense matter.

ON THE GRAPHS OF PRODUCTS OF CONTINUOUS FUNCTIONS AND FRACTAL DIMENSIONS

In this paper,we consider the graph of the product of continuous functions in terms of Hausdorff and packing dimensions.More precisely,we show that,given a real number 1≤β≤2,any real-valued continuous function in C([0,1])can be decomposed into a product of two real-valued continuous functions,each having a graph of Hausdorff dimensionβ.In addition,a product decomposition result for the packing dimension is obtained.This work answers affirmatively two questions raised by Verma and Priyadarshi[14].

Adding dimensions with Lucy-Richardson-Rosen algorithm to incoherent imaging

A novel computational reconstruction method called the Lucy–Richardson–Rosen algorithm(LRRA)for the construction of a single-shot infrared 3D imaging microscope was reported in Opto-Electronic Science.In that study,a commonly available optical element,the Cassegrain objective lens,was used as a coded aperture for 3D imaging using LRRA.Unlike regular coded aperture imaging systems,achieving 3D imaging using commonly available imaging devices leads to the development of hybrid imaging systems where direct and indirect imaging concepts coexist.The development above will make 3D imaging more commonly used in daily life.

Early selection efficiency for fiber dimensions and their relationships with growth and wood quality for Pinus elliotth Engelm.in southern China

A solid understanding of the efficiency of early selection for fiber dimensions is a prerequisite for breeding slash pine(Pinus elliottii Engelm.)with improved properties for pulp and paper products.Genetic correlations between size of fibers,wood quality and growth properties are also important.To accomplish effective early selection for size of fibers and evaluate the impact for wood quality traits and ring widths,core samples were collected from360 trees of 20 open-pollinated Pinus elliottii families from three genetic trials.Cores were measured by SilviScan,and the age trends for phenotypic values,heritability,early-late genetic correlations,and early selection efficiency for fiber dimensions,such as tangential and radial fiber widths,fiber wall thickness and fiber coarseness,and their correlations with microfibril angle(MFA),modulus of elasticity(MOE),wood density and ring width were investigated.Different phenotypic trends were found for tangential and radial fiber widths while fiber coarseness and wall thickness curves were similar.Age trends of heritability based on area-weighted fiber dimensions were different.Low to moderate heritability from pith to bark(~0.5)was found for all fiber dimension across the three sites except for tangential fiber width and wall thickness at the Ganzhou site.Early-late genetic correlations were 0.9 after age of 9 years,and early selection for fiber dimensions could be effective due to strong genetic correlations.Our results showed moderate to strong positive genetic correlations for modulus of elasticity and density with fiber dimensions.The effects on fiber dimensions were weak or moderate when ring width or wood quality traits were selected alone.Estimates of efficiency for early selection indicated that the optimal age for radial fiber width and fiber coarseness was 6-7 years,while for tangential fiber width and wall thickness was 9-10 years.

Transient response of doubly-curved bio-inspired composite shells resting on viscoelastic foundation subject to blast load using improved first-order shear theory and isogeometric approach

Investigating natural-inspired applications is a perennially appealing subject for scientists. The current increase in the speed of natural-origin structure growth may be linked to their superior mechanical properties and environmental resilience. Biological composite structures with helicoidal schemes and designs have remarkable capacities to absorb impact energy and withstand damage. However, there is a dearth of extensive study on the influence of fiber redirection and reorientation inside the matrix of a helicoid structure on its mechanical performance and reactivity. The present study aimed to explore the static and transient responses of a bio-inspired helicoid laminated composite(B-iHLC) shell under the influence of an explosive load using an isomorphic method. The structural integrity of the shell is maintained by a viscoelastic basis known as the Pasternak foundation, which encompasses two coefficients of stiffness and one coefficient of damping. The equilibrium equations governing shell dynamics are obtained by using Hamilton's principle and including the modified first-order shear theory,therefore obviating the need to employ a shear correction factor. The paper's model and approach are validated by doing numerical comparisons with respected publications. The findings of this study may be used in the construction of military and civilian infrastructure in situations when the structure is subjected to severe stresses that might potentially result in catastrophic collapse. The findings of this paper serve as the foundation for several other issues, including geometric optimization and the dynamic response of similar mechanical structures.

A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

Malicious attacks against data are unavoidable in the interconnected,open and shared Energy Internet(EI),Intrusion tolerant techniques are critical to the data security of EI.Existing intrusion tolerant techniques suffered from problems such as low adaptability,policy lag,and difficulty in determining the degree of tolerance.To address these issues,we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas:(1)it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights;and (2)it combines a tournament competition model with incentive weights to obtain optimal strategies for each stage of the game process.Extensive experiments are conducted in the IEEE 39-bus system,whose results demonstrate the feasibility of the incentive weights,confirm the proposed strategy strengthens the system’s ability to tolerate aggression,and improves the dynamic adaptability and response efficiency of the aggression-tolerant system in the case of limited resources.

Timing theory integrated nursing combined behavior change integrated theory of nursing on primiparous influence

BACKGROUND The comprehension and utilization of timing theory and behavior change can offer a more extensive and individualized provision of support and treatment alternatives for primipara.This has the potential to enhance the psychological well-being and overall quality of life for primipara,while also furnishing healthcare providers with efficacious interventions to tackle the psychological and physiological obstacles encountered during the stages of pregnancy and postpartum.AIM To explore the effect of timing theory combined with behavior change on selfefficacy,negative emotions and quality of life in patients with primipara.METHODS A total of 80 primipara cases were selected and admitted to our hospital between August 2020 and May 2022.These cases were divided into two groups,namely the observation group and the control group,with 40 cases in each group.The nursing interventions differed between the two groups,with the control group receiving routine nursing and the observation group receiving integrated nursing based on the timing theory and behavior change.The study aimed to compare the pre-and post-nursing scores of Chinese Perceived Stress Scale(CPSS),Edinburgh Postpartum Depression Scale(EPDS),Self-rating Anxiety Scale(SAS),breast milk knowledge,self-efficacy,and SF-36 quality of life in both groups.RESULTS After nursing,the CPSS,EPDS,and SAS scores of the two groups was significantly lower than that before nursing,and the CPSS,EPDS,and SAS scores of the observation group was significantly lower than that of the control group(P=0.002,P=0.011,and P=0.001 respectively).After nursing,the breastfeeding knowledge mastery,selfefficacy,and SF-36 quality of life scores was significantly higher than that before nursing,and the breastfeeding knowledge mastery(P=0.013),self-efficacy(P=0.008),and SF-36 quality of life(P=0.011)scores of the observation group was significantly higher than that of the control group.CONCLUSION The integration of timing theory and behavior change integrated theory has been found to be an effective approach in alleviating negative mood and stress experienced by primipara individuals,while also enhancing their selfefficacy and overall quality of life.This study focuses on the key concepts of timing theory,behavior change,primipara individuals,negative mood,and quality of life.

Enhancing the resolution of sparse rock property measurements using machine learning and random field theory

The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.

Validation of a Characteristics Dimensions for Transfers during Convective Drying of Sweet Potato Cubic, Cylindrical and Spherical Shapes

This present work solves the problem of initial shape influence on transfer during convective drying. A characteristic dimension is found for the cubic, cylindrical and spherical-shaped samples of the sweet potato. This characteristic dimension corresponds to the diameter D for the sphere, to the edge a for the cube and the diameter = height D = H for the cylinder. Unlike the sphere where this characteristic dimension is perfect, the cubic and cylindrical shapes have space factors which are, among other things, angles and borders. By fixing the same characteristic dimensions, we end up with overlapping curves, showing identical and uniform transfers.

Dimension by Dimension Finite Volume HWENO Method for Hyperbolic Conservation Laws

In this paper,we propose a finite volume Hermite weighted essentially non-oscillatory(HWENO)method based on the dimension by dimension framework to solve hyperbolic conservation laws.It can maintain the high accuracy in the smooth region and obtain the high resolution solution when the discontinuity appears,and it is compact which will be good for giving the numerical boundary conditions.Furthermore,it avoids complicated least square procedure when we implement the genuine two dimensional(2D)finite volume HWENO reconstruction,and it can be regarded as a generalization of the one dimensional(1D)HWENO method.Extensive numerical tests are performed to verify the high resolution and high accuracy of the scheme.

Scalable Temporal Dimension Preserved Tensor Completion for Missing Traffic Data Imputation With Orthogonal Initialization

Dear Editor,This letter puts forward a novel scalable temporal dimension preserved tensor completion model based on orthogonal initialization for missing traffic data(MTD)imputation.The MTD imputation acts directly on accessing the traffic state,and affects the traffic management.

Charge self-consistent dynamical mean field theory calculations incombination with linear combination of numerical atomic orbitalsframework based density functional theory

We present a formalism of charge self-consistent dynamical mean field theory(DMFT)in combination with densityfunctional theory(DFT)within the linear combination of numerical atomic orbitals(LCNAO)framework.We implementedthe charge self-consistent DFT+DMFT formalism by interfacing a full-potential all-electron DFT code with threehybridization expansion-based continuous-time quantum Monte Carlo impurity solvers.The benchmarks on several 3d,4fand 5f strongly correlated electron systems validated our formalism and implementation.Furthermore,within the LCANOframework,our formalism is general and the code architecture is extensible,so it can work as a bridge merging differentLCNAO DFT packages and impurity solvers to do charge self-consistent DFT+DMFT calculations.

Intelligent Transformation: General Intelligence Theory

This paper aims to formalize a general definition of intelligence beyond human intelligence. We accomplish this by re-imagining the concept of equality as a fundamental abstraction for relation. We discover that the concept of equality = limits the sensitivity of our mathematics to abstract relationships. We propose a new relation principle that does not rely on the concept of equality but is consistent with existing mathematical abstractions. In essence, this paper proposes a conceptual framework for general interaction and argues that this framework is also an abstraction that satisfies the definition of Intelligence. Hence, we define intelligence as a formalization of generality, represented by the abstraction ∆∞Ο, where each symbol represents the concepts infinitesimal, infinite, and finite respectively. In essence, this paper proposes a General Language Model (GLM), where the abstraction ∆∞Ο represents the foundational relationship of the model. This relation is colloquially termed “The theory of everything”.

Microstructure Characterization of Bubbles in Gassy Soil Based on the Fractal Theory

The microscopic characterization of isolated bubbles in gassy soil plays an important role in the macroscopic physical properties of sediments and is a key factor in the study of geological hazards in gas-bearing strata.Based on the box-counting method and the pore fractal features in porous media,a fractal model of bubble microstructure parameters in gassy soil under different gas con-tents and vertical load conditions is established by using an industrial X-ray CT scanning system.The results show that the fractal di-mension of bubbles in the sample is correlated with the volume fraction of bubbles,and it is also restricted by the vertical load.The three-dimensional fractal dimension of the sample is about 1 larger than the average two-dimensional fractal dimension of all the slices from the same sample.The uniform porous media fractal model is used to test the equivalent diameter,and the results show that the variation of the measured pore diameter ratio is jointly restricted by the volume fraction and the vertical load.In addition,the measured self-similarity interval of the bubble area distribution is tested by the porous media fractal capillary bundle model,and the fitting curve of measured pore area ratio in a small loading range is obtained in this paper.