Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

DYNAMIC ANALYSIS OF A TYPE OF FINANCIAL RISK CONTAGION MODEL INVOLVING IMMUNITY PERIOD AND SELF-RESCUE

In this paper,we study the dynamics of a Susceptible-Exposed-Infectious-Recovered(SEIR)nancial risk contagion model with time delay.Using stability theory and Hopf bifurcation theory,equilibria stability and Hopf bifurcation are analyzed in detail.Based on the epidemic model,we improve it by taking prior prevention and self-rescue into consideration,conclude pre-ventive intensity and self-rescue capabilities e ect the number of infections.At the same time,the analytical conditions for Hopf bifurcation are obtained,and the relevant results are veri ed by numerical simulations.

Theoretical characterization of the temperature-dependent saturation magnetization of magnetic metallic materials

Based on the force-heat equivalence energy density principle,a theoretical model for magnetic metallic materials is developed,which characterizes the temperature-dependent magnetic anisotropy energy by considering the equivalent relationship between magnetic anisotropy energy and heat energy;then the relationship between the magnetic anisotropy constant and saturation magnetization is considered.Finally,we formulate a temperature-dependent model for saturation magnetization,revealing the inherent relationship between temperature and saturation magnetization.Our model predicts the saturation magnetization for nine different magnetic metallic materials at different temperatures,exhibiting satisfactory agreement with experimental data.Additionally,the experimental data used as reference points are at or near room temperature.Compared to other phenomenological theoretical models,this model is considerably more accessible than the data required at 0 K.The index included in our model is set to a constant value,which is equal to 10/3 for materials other than Fe,Co,and Ni.For transition metals(Fe,Co,and Ni in this paper),the index is 6 in the range of 0 K to 0.65T_(cr)(T_(cr) is the critical temperature),and 3 in the range of 0.65T_(cr) to T_(cr),unlike other models where the adjustable parameters vary according to each material.In addition,our model provides a new way to design and evaluate magnetic metallic materials with superior magnetic properties over a wide range of temperatures.

IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

Path-dependent speciation in dynamic fitness landscapes

Species is a fundamental concept in evolutionary biology and biodiversity.However,existing species definitions are often influenced by artificial factors or are challenging in practical application,leading to confusion in species classification.Due to uncertain environmental changes and random genetic drift,the fitness expectations of a population may shift,causing species to evolve to a new evolutionary state based on their current instantaneous fitness within a dynamic fitness landscape.This contrasts with the classic static fitness landscape,where fitness expectations are constant.In a dynamic fitness landscape,speciation may exhibit path dependence,where the evolution of traits follows a probabilistic path,creating feedback that shapes evolutionary trajectories.The path-dependent evolutionary mechanism suggests that species survival within an ecosystem is not directly determined by their fitness but by the probability of their evolutionary pathways.This model also indicates that species can coexist with varying probabilities under limited environmental pressures.Consequently,new species,cryptic species,or sympatric species may emerge via path-dependent evolutionary processes.Within this framework,we developed a mathematical species concept,which may guide future species classification methodologies.

Magnetohydrodynamic Conjugate Free Convective Heat Transfer Analysis of an Isothermal Horizontal Circular Cylinder with Temperature Dependent Viscosity

Heat transfers due to MHD-conjugate free convection from the isothermal horizontal circular cylinder while viscosity is a function of temperature is investigated. The governing equations of the flow and connected boundary conditions are made dimensionless using a set of non-dimensional parameters. The governing equations are solved numerically using the finite difference method. Numerical results are obtained for various values of viscosity variation parameter, Prandtl number, magnetic parameter, and conjugate conduction parameter for the velocity and the temperature within the boundary layer as well as the skin friction coefficients and heat transfer rate along the surface.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

Predictions in Clinical Efficiency of SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp) Inhibitors by Molecular Docking

This study utilizes the enzyme-substrate complex theory to predict the clinical efficacy of COVID-19 treatments at the biological systems level, using molecular docking stability indicators. Experimental data from the Protein Data Bank and molecular structures generated by AlphaFold 3 were used to create macromolecular complex templates. Six templates were developed, including the holo nsp7-nsp8-nsp12 (RNA-dependent RNA polymerase) complex with dsRNA primers (holo-RdRp-RNA). The study evaluated several ligands—Favipiravir-RTP, Remdesivir, Abacavir, Ribavirin, and Oseltamivir—as potential viral RNA polymerase inhibitors. Notably, the first four of these ligands have been clinically employed in the treatment of COVID-19, allowing for comparative analysis. Molecular docking simulations were performed using AutoDock 4, and statistical differences were assessed through t-tests and Mann-Whitney U tests. A review of the literature on COVID-19 treatment outcomes and inhibitors targeting RNA polymerase enzymes was conducted, and the inhibitors were ranked according to their clinical efficacy: Remdesivir > Favipiravir-RTP > Oseltamivir. Docking results obtained from the second and third templates aligned with clinical observations. Furthermore, Abacavir demonstrated a predicted efficacy comparable to Favipiravir-RTP, while Ribavirin exhibited a predicted efficacy similar to that of Remdesivir. This research, focused on inhibitors of SARS-CoV-2 RNA-dependent RNA polymerase, establishes a framework for screening AI-generated drug templates based on clinical outcomes. Additionally, it develops a drug screening platform based on molecular docking binding energy, enabling the evaluation of novel or repurposed drugs and potentially accelerating the drug development process.

A Study of Radiation-Induced Telomere Instability Using Multiplex Ligation-Dependent Probe Amplification (MLPA)

The integrity of the chromosomes for two WIL2-derived lymphoblastoid cell lines (TK6 and WTK1) in the presence and absence of ionizing radiation was analyzed by Multiplex Ligation-Dependent Probe Amplification (MLPA). The TK6 cell line has the native p53 tumor-suppressor gene, whereas WTK1 cells contain a p53 mutation. Each cell line was isolated pre- and post-irradiation (2 and 3 Gy) and analyzed by MLPA. The impact of irradiation on these two cell lines was investigated using probes that target specific regions on chromosomes associated with subtelomeric regions. Results indicate that WTK1 and TK6 are impacted differently after irradiation, and that each cell line presents its own unique MLPA profile. The most notable differences are the appearance of a number of probes in the post-irradiated MLPA profile that are not present in the controls, and two unique probe signals only seen in WTK1 cells. These results build on our previous studies that indicate how different human cell lines can be affected by radiation in significantly different ways depending on the presence or absence of wild type p53.

Inverse Spectral Problem for Sturm-Liouville Operator with Boundary and Jump Conditions Dependent on the Spectral Parameter

In this paper, the inverse spectral problem of Sturm-Liouville operator with boundary conditions and jump conditions dependent on the spectral parameter is investigated. Firstly, the self-adjointness of the problem and the eigenvalue properties are given, then the asymptotic formulas of eigenvalues and eigenfunctions are presented. Finally, the uniqueness theorems of the corresponding inverse problems are given by Weyl function theory and inverse spectral data approach.

Thermomechanical Dynamics (TMD) and Bifurcation-Integration Solutions in Nonlinear Differential Equations with Time-Dependent Coefficients

The new independent solutions of the nonlinear differential equation with time-dependent coefficients (NDE-TC) are discussed, for the first time, by employing experimental device called a drinking bird whose simple back-and-forth motion develops into water drinking motion. The solution to a drinking bird equation of motion manifests itself the transition from thermodynamic equilibrium to nonequilibrium irreversible states. The independent solution signifying a nonequilibrium thermal state seems to be constructed as if two independent bifurcation solutions are synthesized, and so, the solution is tentatively termed as the bifurcation-integration solution. The bifurcation-integration solution expresses the transition from mechanical and thermodynamic equilibrium to a nonequilibrium irreversible state, which is explicitly shown by the nonlinear differential equation with time-dependent coefficients (NDE-TC). The analysis established a new theoretical approach to nonequilibrium irreversible states, thermomechanical dynamics (TMD). The TMD method enables one to obtain thermodynamically consistent and time-dependent progresses of thermodynamic quantities, by employing the bifurcation-integration solutions of NDE-TC. We hope that the basic properties of bifurcation-integration solutions will be studied and investigated further in mathematics, physics, chemistry and nonlinear sciences in general.

Reliability assessment considering dependent competing failure process and shifting-threshold

The reliability assessment problem for products subject to degradation and random shocks is investigated. Two kinds of probabilistic models are constructed, in which the dependent competing failure process is considered. First, based on the assumption of cumulative shock, the probabilistic models for hard failure and soft failure are built respectively. On this basis, the dependent competing failure model involving degradation and shock processes is established. Furthermore, the situation of the shifting-threshold is also considered, in which the hard failure threshold value decreases to a lower level after the arrival of a certain number of shocks. A case study of fatigue crack growth is given to illustrate the proposed models. Numerical results show that shock has a significant effect on the failure process; meanwhile, the effect will be magnified when the value of the hard threshold shifts to a lower level.

Substrate-dependent photoreactivities of BiOBr nanoplates prepared at different pH values

In this study,we showed that BiO Br nanoplates prepared at different pH values have substratedependent photocatalytic activities under visible-light irradiation. The BiO Br nanoplates synthesized at pH 1（BOB-1） degraded salicylic acid more effectively than did those obtained at pH 3（BOB-3）,but the order of their photocatalytic activities in rhodamine B（RhB） degradation were reversed. Electrochemical Mott–Schottky and zeta-potential measurements showed that BOB-1 had a more positive valence band and lower surface charge,leading to superior photocatalytic activity in salicylic acid degradation under visible light. However,BOB-3 was more powerful in RhB degradation because larger numbers of superoxide radicals were generated via electron injection from the excited RhB to its more negative conduction band under visible-light irradiation; this was confirmed using active oxygen species measurements and electron spin resonance analysis. This study deepens our understanding of the origins of organic-pollutant-dependent photoreactivities of semiconductors,and will help in designing highly active photocatalysts for environmental remediation.

Time Dependent Ginzburg-Landau方程的Weierstrass椭圆函数解

将文[22]中提出的求解非线性演化方程的Weierstrass椭圆函数解的一个新方法应用于Time De-pendent Ginzburg-Landau方程,获得了该方程的一些新的双周期解,并在退化情形下得到了一些新的精确孤波解.

Involvement of Calcium dependent Protein Kinases in ABA regulation of Stomatal Movement

Patch clamp techniques were employed to investigate if calcium dependent protein kinases (CDPKs) be involved in the signal transduction pathways of stomatal movement regulation by the phytohormone abscisic acid (ABA) in Vicia faba. Stomatal opening was completely inhibited by external application of 1 μmol/L ABA, and such ABA inhibition was significantly reversed by the addition of CDPK inhibitor trifluoperazine (TFP). The inward whole cell K + currents were inhibited by 60% in the presence of 1 μmol/L intracellular ABA, and this inhibition was completely abolished by the addition of CDPK competitive substrate histone Ⅲ S. The results suggest that CDPKs may be involved in the signal transduction cascades of ABA regulated stomatal movements.

Algebraic processing technique for extracting frequency-dependent shear-wave splitting parameters in an anisotropic medium

Based on the dual source cumulative rotation technique in the time-domain proposed by Zeng and MacBeth（1993）,a new algebraic processing technique for extracting shear-wave splitting parameters from multi-component VSP data in frequency-dependent medium has been developed.By using this dual source cumulative rotation technique in the frequency-domain（DCTF）,anisotropic parameters,including polarization direction of the shear-waves and timedelay between the fast and slow shear-waves,can be estimated for each frequency component in the frequency domain.It avoids the possible error which comes from using a narrow-band filter in the current commonly used method.By using synthetic seismograms,the feasibility and validity of the technique was tested and a comparison with the currently used method was also given.The results demonstrate that the shear-wave splitting parameters frequency dependence can be extracted directly from four-component seismic data using the DCTF.In the presence of larger scale fractures,substantial frequency dependence would be found in the seismic frequency range,which implies that dispersion would occur at seismic frequencies.Our study shows that shear-wave anisotropy decreases as frequency increases.

Uniform asymptotics for finite-time ruin probability in some dependent compound risk models with constant interest rate

Consider two dependent renewal risk models with constant interest rate. By using some methods in the risk theory, uniform asymptotics for finite-time ruin probability is derived in a non-compound risk model, where claim sizes are upper tail asymptotically independent random variables with dominatedly varying tails, claim inter-arrival times follow the widely lower orthant dependent structure, and the total amount of premiums is a nonnegative stochastic process. Based on the obtained result, using the method of analysis for the tail probability of random sums, a similar result in a more complex and reasonable compound risk model is also obtained, where individual claim sizes are specialized to be extended negatively dependent and accident inter-arrival times are still widely lower orthant dependent, and both the claim sizes and the claim number have dominatedly varying tails.

Spin-Unrestricted Multi-Configuration Time-Dependent Hartree Fock Theory

Based on spin-unrestricted hartree fock theory, we present the spin unrestricted multi- configuration time dependent hartree lock theory （UMCTDHF） to describe the electron correlation dynamics of systems interacting with laser field. The positive spin orbitals and the negative spin orbitals are propagated in their own subspace respectively. The spin orbital in the spin-down subspace acts with that in the spin-up subspace by the reduced density matrix and mean field operator. The ground energy is acquired by propagating the trial wave function in the imaginary time by using spin-restricted MCTDHF （RMCTDHF） and UMCTDHF respectively. Then the ionization probabilities and the electrons energies are calculated by using RMCTDHF and UMCTDHF when the laser field is present. The ionization probability calculated with UMCTDHF agrees with the previous theoretical reports very well. The UMCTDHF method is accurate and applicable for open shell system beyond the capability of the RMCTDHF method.

水泥固化铅污染粘土的pH-Dependent试验研究

通过pH-dependent试验,研究水泥固化铅污染土的溶出特性.对滤出液pH的研究结果表明,滤出液pH随加酸量增加而下降,且试样C12Pb2较C12Pb0、试样C18Pb2较C18Pb0的碱性/酸缓冲能力弱.对滤出液中铅浓度([Pb])随滤出液pH、水泥掺量的变化特征进行分析,结果表明,[Pb]随滤出液pH增大而先减小后增加;且试样C18Pb2较C12Pb2,其溶出的[Pb]显著减小,铅最大溶出率小5个百分点,表明水泥掺量的增大使得水泥对铅的固定效果更好,使固化土中可溶出的铅减少.