Quantitative Relation Research Articles

Damage monitoring on inter-lamination of GFRP via the resistance change of the MWCNT@GF sensor

The paper aimed to investigate the performance of multi-walled carbon nanotube-coated GF (MWCNT@GF) sensors on interlayer shear damage monitoring and sensing capability of glass fiber-reinforced polymers (GFRPs) based on the resistance change under short beam shear (SBS) load. The MWCNT@GF sensor, manufactured by physical vapor deposition (PVD), was embedded into the neutral layer of laminates to form an in-situ sensing network in different directions and positions. “The MWCNT@GF sensor, manufactured by physical vapor deposition (PVD), was embedded into the neutral layer of laminates to form an in-situ sensing network.” “With the help of Keithley 2700 programmable electrometer and the 3D-digital image correlation(3D-DIC), monotonic and cyclic tests were carried out.” The monotonic test found that the off-axis sensor is more sensitive to shear failure than the on-axis sensor because of its lower shear strength. In addition, the qualitative relationship between shear damage and relative resistance was established by selecting crucial moments. In the cyclical test, the relative resistance of off-axis sensors presented a cyclic mode under cyclic load. Furthermore, the relative resistance under the first 20 cyclic loads was similar to that under monotonic loads. “Furthermore, the relative resistance under the first 20 cyclic loads was similar to that under monotonic loads, which shows that the sensor has superior sensing ability. Finally, the quantitative relation between shear damage and relative resistance was established.” “That means MWCNT@GF sensors can be used to reasonably evaluate the damage state and further evaluate the service performance, reliability and remaining life of the structure.”

Influence of milling stability on machined surface integrity and fatigue performance of Ti-6Al-4V titanium alloy

Chatter is a deciding factor in milling operations regarding surface integrity and production efficiency. The purpose of this experimental research is to systematically investigate the influence of milling stability on machined surface integrity and fatigue performance of Ti-6Al-4V alloy samples. The surface integrity parameters like roughness, plastic deformation, microhardness, and residual stress were used to evaluate the machined surface quality. The fatigue tests were performed at five tensile stress levels with samples machined under stable, critical stable and unstable (chatter) cutting conditions. The experimental findings show that in comparison with samples produced by stable milling, the machined surface integrity parameters get worse with the increase of chatter amplitude and chatter marks, while fatigue test results show that the average fatigue life of these samples also decreases by about 20 %. The fatigue fracture morphology underscored that multiple fatigue cracks are initiated from the chatter marks on the machined surface. The experimental results provide a quantitative relation between the occurrence of chatter in milling operations and the life expectancy of the corresponding machined parts.

Data-driven design of novel lightweight refractory high-entropy alloys with superb hardness and corrosion resistance

Lightweight refractory high-entropy alloys (LW-RHEAs) hold significant potential in the fields of aviation, aerospace, and nuclear energy due to their low density, high strength, high hardness, and corrosion resistance. However, the enormous composition space has severely hindered the development of novel LW-RHEAs with excellent comprehensive performance. In this paper, an machine learning (ML)-based alloy design strategy combined with a multi-objective optimization method was proposed and applied for a rational design of Al-Nb-Ti-V-Zr-Cr-Mo-Hf LW-RHEAs. The quantitative relation of “composition-structure-property” was first established by ML modeling. Then, feature analysis reveals that Cr content greater than 12 at.% is a key criterion for alloys with high corrosion resistance. The phase structure, density, melting point, hardness and corrosion resistance of the alloys were screened layer by layer, and finally, three LW-RHEAs with superb hard and corrosion resistance were successfully designed. Key experimental validation indicates that three target alloys have densities around 6.5 g/cm3, and all alloys are disordered bcc_A2 single-phase with the highest hardness of 593 HV and the largest pitting potential of 2.5 VSCE, which far exceeds all the literature reports. The successful demonstration in this paper clearly demonstrates that the present design strategy driven by the ML technique should be generally applicable to other RHEA systems.

Development of Imidazo[1,2-a]pyridines Containing Sulfonyl Piperazines as Potential Antivirals against Tomato Spotted Wilt Virus.

Mesoionic structures have become important advancements in recent agrochemical design. However, their potential beyond serving as excellent insecticides remains unexplored with limited reports available. Herein, a series of imidazo[1,2-a]pyridine mesoionics were developed by structurally incorporating sulfonyl piperazine moieties into imidazo[1,2-a]pyridines. Many of the obtained derivatives demonstrated bioactivity against tomato spotted wilt virus (TSWV) in bioassays. In particular, compound Z40, identified via three-dimensional quantitative structure activity relation models, displayed encouraging protective performance (half-maximal effect concentration = 252 μg/mL) compared to the positive controls ningnanmycin (332 μg/mL) and vanisulfane (523 μg/mL). Through defense enzyme assays, real-time quantitative polymerase chain reaction, and proteomics analysis, Z40 was identified as a plant immunomodulator that promotes defense enzyme activity and the mediates oxidative phosphorylation pathway, enabling plants to resist TSWV. We expect this study to help expand the possibilities of mesoionic compounds.

Fitting Quality of NMR Relaxation Data to Differentiate Asphalt Binders

Asphalt binder performance grades (PGs) are important metrics in designing pavements for effective transportation infrastructure. The PG system relies on the binder’s stiffness and is determined through energy- and time-intensive physical testing. Physical properties, like stiffness, can also be determined by spin–lattice NMR relaxometry, a non-destructive chemical method. NMR relaxometry can quantify the molecular mobility of materials by determining relaxation times from exponential decays of excited nuclear magnetization. While relaxation times have been used to determine physical properties of materials, a quantitative relation to the PG grades of asphalt binder is yet to be established. In this study, T1 NMR relaxation analyses were used to differentiate between solid asphalt binders and determine the fastest yet still-reliable method of modeling exponential decay data. Algorithms that fit exponential decay relaxation data using one, two, or three independent relaxation times were compared with a 128-coefficient discrete inverse Laplace transformation to determine the best mathematical fit for a comparative analysis. The number of data points was then reduced from 256 to 64 to 16 and finally to 8 data points on a relaxation curve to reduce the testing time and determine the minimum number of data points needed for comparison. Two batches of PG 64-22 asphalt binder, along with samples of PG 76-22 and 94-10 binders, were investigated. The best compromise between measuring time and data reliability was found by acquiring 64 data points and then using a biexponential model to fit the experimental data. The PG 64-22 sources provided similar results, indicating similar physical properties. The PG 64-22 and PG 76-22 binders could also be compared via monoexponential data fits, but the PG 94-10 samples required an additional relaxation parameter for comparison. To differentiate all three binder grades, the primary relaxation times, along with their relative ratios, were utilized.

Improving the Efficiency of Software Reliability Demonstration Testing by Introducing Testing Effectiveness

For highly reliable software systems, it is expensive, time consuming, or even infeasible to perform reliability testing via a conventional software reliability demonstration testing (SRDT) plan. Moreover, in the traditional SRDT approach, the various characteristics of the software system or test sets are not considered when making the testing schemes. Some studies have focused on the effect of software testability on SRDT, but only limited situations were discussed, and many theoretical and practical problems have been left unresolved. In this paper, an extended study on the quantitative relation between test effectiveness (TE) and test effort for SRDT is proposed. Theoretical derivation is put forward by performing statistical analysis for the test suite according to TE. The combinations of all the cases of zero-failure and revealed nonzero failure, as well as discrete-type software and continuous-type software, are studied with the corresponding failure probability models constructed. That is, zero-failure and nonzero failure, as well as discrete-type software and continuous-type software, respectively, constitute the symmetry and asymmetry of SRDT. Finally, we illustrated all the models and performed applications on the Siemens program suite. The experimental results show that within the same limitation of requirements and confidence levels, this approach can effectively reduce the number of test cases and the test duration, i.e., accelerate the test process and improve the efficiency of the SRDT.

Numerical evaluation of vertical and horizontal distances for nitrogen attenuation from Onsite Sewage treatment and disposal systems (OSTDS)

Onsite Sewage Treatment and Disposal Systems (OSTDS) used for domestic wastewater treatment are a source of nitrogen (ammonium and nitrate) contamination to groundwater and surface water. One way to manage the contamination is to establish setback distances for nitrogen attenuation through nitrification and denitrification reactions within the setback distances. Determining the setback distances requires investigating nitrogen attenuation as a function of distance from OSTDS. While field investigations have been conducted, there have been few modeling investigations. Using an ArcGIS-based Nitrogen Load Estimation Toolkit, this study simulates nitrogen attenuation for over 20,000 OSTDS at five study areas across Florida, where a third of households are served by OSTDS. Different from conventional studies that only consider the horizontal distances (between an OSTDS and a surface water body that receives OSTDS effluents), this study also considers the vertical distances (between an OSTDS drainfield and water table beneath the drainfield) to account for the nitrogen reactive transport processes in the vadose zones and groundwater aquifers, making the assessment of nitrogen attenuation more comprehensive. Modeling results yield the following three empirical but quantitative relations: (1) vertical attenuation rate as a function of vertical distance and saturated hydraulic conductivity (Ks) available in the Soil Survey Geographic Database, (2) horizontal attenuation rate as a function of horizontal distance and Ks, (3) total attenuation rate as a multiplication of the vertical and horizontal attenuation rates. These relations can be used to determine nitrogen attenuation within vertical and horizontal distances to OSTDS for practical management of OSTDS nitrogen contamination.

Revisiting the strain rate sensitivity of the flow stress of copper: Theory and experiment

One of the most important issues related to the strength of metals is the strain rate sensitivity of the flow stress. In this study, an analytical model of the flow stress as a function of strain rate is derived theoretically. The model can reproduce the strain rate sensitivity of the flow stress of copper over a wide range of strain rates (up to 109 s−1) quantitatively. Our theoretical derivations indicate that the strain rate sensitivity of the flow stress, especially that above 103 s−1, is a result of both the variation of the dislocation mobility mechanism with stress and the particular stress dependence of dislocation density but is not a result of each single mechanism. In particular, the stress dependence of the dislocation density and the initial dislocation density are critical to the quantitative relation of the flow stress–strain rate at high strain rate and the strain rate threshold, under which the upturn of the flow stress occurs, respectively. Moreover, experiments with copper of different initial dislocation densities at moderate and high strain rate are performed. The strain rate threshold of the flow stress upturn observed in the experiments grows considerably as initial dislocation density increases, which is in accordance with theoretical prediction by our model.

Generation of the radial higher-order orbital angular momentum mode in helically twisted elliptic fiber.

The generation mechanism and regulation method of the radial higher-order orbital angular momentum (OAM) mode based on helically twisted elliptic fiber (HTEF) are investigated. This work aims to reveal the quantitative relation between the twisted rate (α) and the target radial higher-order OAM mode. From theoretical simulations, it is concluded that α is the key to regulating the radial higher-order OAM mode. In the experiment, OAM2n modes with radial higher-order n of 2, 3, 4, and 5 are successfully generated at 1550 nm by regulating α of the HTEF. Finally, the transmission spectrum and purity measurements are performed for the OAM24 mode, and it can be concluded that the fabricated experimental samples have more than 90% conversion efficiency and close to 94% purity under the appropriate α and twisted length.

Analytical method of incorporating failure probability to predict the fatigue life of ultra-high-performance concrete (UHPC)

This study predicted the fatigue life (N) of UHPC incorporated with different volume fractions (Vf = 0.0%, 0.5%, 1.0%, 1.5% and 2.0%) of steel fiber under flexural cyclic loading at various stress levels (S). The Weibull distribution, a two-parameter model, was utilized to estimate the distribution of fatigue life in UHPC. Subsequently, three methods were employed to calculate the parameters: the graphical method, the method of moments, and the method of maximum likelihood. The averaged values of these parameters were then obtained to enhance the accuracy of the estimation. The results are presented in the form of S-N diagrams, which depict the quantitative relationship between stress (S) and fatigue life (N). This relationship was determined using the Wohler equation, the modified Wohler equation, and the power equation. By employing these equations, the flexural fatigue strength of UHPC can be accurately predicted. Subsequently, the fatigue failure probability (Pf) was incorporated to enhance the reliability of the S-N quantitative relation. The fatigue testing results were presented in the form of S-N-Pf curves, which comprehensively reflect the relationship between stress, fatigue life, and failure probability. Furthermore, the mathematical relation of the S-N-Pf curves was derived to predict the fatigue life of UHPC with a given failure probability, providing a more comprehensive and accurate assessment of its fatigue behavior.

Relation between photoionisation cross sections and attosecond time delays

Abstract Determination and interpretation of Wigner-like photoionisation delays is one of the most active fields of attosecond science. Previous results have suggested that large photoionisation delays are associated with structured continua, but a quantitative relation between photoionisation cross sections and time delays has been missing. Here, we derive a Kramers-Kronig-like relation between these quantities and demonstrate its validity for (anti)resonances. This new concept defines a topological analysis, which rationalises the sign of photoionisation delays and thereby sheds new light on a long-standing controversy regarding the sign of the photoionisation delay near the Ar 3s Cooper minimum. Our work bridges traditional photoionisation spectroscopy with attosecond chronoscopy and offers new methods for analysing and interpreting photoionisation delays.

Development of computational thinking of students – future teachers by means of solving problems on the processing of structured data

The problem and the purpose. Computational thinking is one of the categories that currently assesses the quality of specialist training, including that of a future teacher. The mentor of a digital school needs computational thinking skills for the successful implementation of work functions and for determining the trajectory of his personal development. The purpose of the study is to identify the possibilities of structured data processing tools for the development of computational thinking of future teachers. Research methods. Structured data is information organized in the form of tables and files of other formats. The research was conducted on the basis of Vyatka State University (Russian Federation). The experiment involved 330 students studying in the field of training: 44.03.05 Pedagogical studies (with two specialties). The use of structured data processing tools was purposefully carried out in the classes of the design discipline from the block “Digital technologies in education”. A set of techniques was used to determine the level of computational thinking such as “Geometric figures”, “Quantitative relations”, “Complex analogies”. For statistical processing of data, Pearson's χ2 (chi-square) criterion is used. Results. Interaction in the experimental group was implemented in stages: the study of basic tools; development of skills of graphical interpretation; the use of functions that allow analyzing and protecting the contents of structured data. The features of the proposed information interaction are: students with different educational paths are involved; the technology of reasoned discourse is applied at every stage. Statistically significant differences were revealed in the qualitative changes that occurred in the pedagogical system (χ2 = 7.024; p < 0.05). Conclusion. The tasks on the processing of structured data that maximize the development of computational thinking are formulated: conditional formatting; establishing links between the source data and the result; automatic recalculation of the result; filtering, sorting, etc. The difficulties that complicate the use of the proposed innovations are defined: how to state a task and to adapt it to the specifics of the field of training; how to organize a reasoned discourse.

Reduced-order reconstruction of discrete grey forecasting model and its application

Discrete grey forecasting models based on an accumulative operator have been widely used in many practical fields. With the development of grey forecasting models, it is a problem to be solved to further analyze internal mechanisms and unify the structures. This paper aims to reconstruct the model from a perspective of sequence characteristics and simplify the modeling steps under the condition of ensuring the accuracy of the model. First, this paper analyzes dynamic sequence evolution hidden and mines relationship between the structure and original sequence features contained in discrete grey forecasting model. Then, the reconstruction is carried out to prove the equivalence and quantitative relation between reduced-order model and original model. Under order recursive estimation, new parameters are addressed. Finally, theoretical correctness is verified by large-scale numerical simulation. Moreover, the reduced-order model is applied for prediction on the peak of battery incremental capacity and capacity degradation. Results show the effectiveness and superior prediction performance of the reduced-order model, where MAPEs of grey forecasting models have controlled under 4%.

Dynamics and Diagnosis of Independent Thinking Processes of Students (on the Example of the First Teenagers)

The article describes, creative, modular technologies for improving the socio-psychological mechanisms of the development of independent thinking of adolescent students are included in the practice. The following methodologies were used, which were considered subtests of the scientific and theoretical sources on the topic, comparative analysis, observation, question and answer, conversation, Wexler and Amtxauer methodologies: methodology "separation of important characters", methodology "quantitative relations", methodology of "intellectual disability", methodology "complex analogy", conducting training sessions on advanced pedagogical technologies in order to determine the psychological impact,generalization of mathematical-statistical results in order to prove the scientific value of empirical materials. Theoretical and practical significance of the study: scientific-theoretical justification of the problem of independent thinking of adolescents; identification of its specific psychological and pedagogical characteristics; identification of the content, forms and methods of independent thinking of adolescents, the development of its holistic system; development of criteria aimed at determining effective forms of independent thinking of adolescents, as well as scientifically based conclusions and recommendations on The practical significance of the study is that the ideas advanced in it can be used in the study of general secondary education schools “sense of Homeland”, “literature” (grades 5-6) educational subjects, a special course “independent thinking of adolescents”, Physical Education, Higher and secondary specialized vocational education institutions, teachers ' training and retraining institutes “pedagogy”, “psychology of young Times”.

AI-driven Discovery of Morphomolecular Signatures in Toxicology.

Early identification of drug toxicity is essential yet challenging in drug development. At the preclinical stage, toxicity is assessed with histopathological examination of tissue sections from animal models to detect morphological lesions. To complement this analysis, toxicogenomics is increasingly employed to understand the mechanism of action of the compound and ultimately identify lesion-specific safety biomarkers for which in vitro assays can be designed. However, existing works that aim to identify morphological correlates of expression changes rely on qualitative or semi-quantitative morphological characterization and remain limited in scale or morphological diversity. Artificial intelligence (AI) offers a promising approach for quantitatively modeling this relationship at an unprecedented scale. Here, we introduce GEESE, an AI model designed to impute morphomolecular signatures in toxicology data. Our model was trained to predict 1,536 gene targets on a cohort of 8,231 hematoxylin and eosin-stained liver sections from Rattus norvegicus across 127 preclinical toxicity studies. The model, evaluated on 2,002 tissue sections from 29 held-out studies, can yield pseudo-spatially resolved gene expression maps, which we correlate with six key drug-induced liver injuries (DILI). From the resulting 25 million lesion-expression pairs, we established quantitative relations between up and downregulated genes and lesions. Validation of these signatures against toxicogenomic databases, pathway enrichment analyses, and human hepatocyte cell lines asserted their relevance. Overall, our study introduces new methods for characterizing toxicity at an unprecedented scale and granularity, paving the way for AI-driven discovery of toxicity biomarkers.

2,5-Dimethoxy-4-iodoamphetamine and altanserin induce region-specific shifts in dopamine and serotonin metabolization pathways in the rat brain

PurposeFor understanding the neurochemical mechanism of neuropsychiatric conditions associated with cognitive deficits it is of major relevance to elucidate the influence of serotonin (5-HT) agonists and antagonists on memory function as well dopamine (DA) and 5-HT release and metabolism. In the present study, we assessed the effects of the 5-HT2A receptor agonist 2,5-dimethoxy-4-iodoamphetamine (DOI) and the 5-HT2A receptor altanserin (ALT) on object and place recognition memory and cerebral neurotransmitters and metabolites in the rat. MethodsRats underwent a 5-min exploration trial in an open field with two identical objects. After systemic injection of a single dose of either DOI (0.1 mg/kg), ALT (1 mg/kg) or the respectice vehicle (0.9 % NaCl, 50 % DMSO), rats underwent a 5-min test trial with one of the objects replaced by a novel one and the other object transferred to a novel place. Upon the assessment of object exploration and motor/exploratory behaviors, rats were sacrificed. DA, 5-HT and metabolite levels were analyzed in cingulate (CING), caudateputamen (CP), nucleus accumbens (NAC), thalamus (THAL), dorsal (dHIPP) and ventral hippocampus (vHIPP), brainstem and cerebellum with high performance liquid chromatography. ResultsDOI decreased rearing but increased head-shoulder motility relative to vehicle. Memory for object and place after both DOI and ALT was not different from vehicle. Network analyses indicated that DOI inhibited DA metabolization in CING, CP, NAC, and THAL, but facilitated it in dHIPP. Likewise, DOI inhibited 5-HT metabolization in CING, NAC, and THAL. ALT facilitated DA metabolization in the CING, NAC, dHIPP, vHIPP, and CER, but inhibited it in the THAL. Additionally, ALT facilitated 5-HT metabolization in NAC and dHIPP. ConclusionsDOI and ALT differentially altered the quantitative relations between the neurotransmitter/metabolite levels in the individual brain regions, by inducing region-specific shifts in the metabolization pathways. Findings are relevant for understanding the neurochemistry underlying DAergic and/or 5-HTergic dysfunction in neurological and psychiatric conditions.

P-390 The percentage of regulatory T cells is associated with T follicular helper cell quantity in the peripheral blood of pregnant women

Abstract Study question Is there a relationship between the percentage of peripheral regulatory T cells (Treg) and other T cell subtypes in the first trimester of pregnancy? Summary answer The percentage of Treg cells showed a significant positive correlation with the quantity of T follicular helper cells (TFH). What is known already Regulatory T cells (Treg) play an essential role in the process of embryo implantation and maintenance of normal pregnancy. The quantity of these cells in the peripheral blood expands during the first trimester of pregnancy. Several studies report the importance of Treg in the control of the inflammatory process and in the pathophysiology of common adverse pregnancy outcomes. However, there is a scarce data about the quantitative relation between Treg and other important T sub-types during pregnancy. Study design, size, duration This is an observational study of 93 women, 28 to 53 years of age (mean 38 years), who had a blood sample during the first trimester (at 8-10 weeks of pregnancy). The study was conducted between November 2022 and October 2023. The exclusion criteria were history of recent inflammatory or infection disorders, recent antibiotic treatment, autoimmune diseases, oncological diseases, moderate or severe endometriosis, and endometrial polyps. Written informed consent was obtained from each participant. Participants/materials, setting, methods SIx peripheral T cell subtypes were measured by flow cytometry: T helpers % (CD3+CD4+CD8-/CD3+), T killers % (CD3+CD4-CD8+/CD3+), double-positive T cells % (CD3+CD4+CD8+/CD3+), double-negative T cells % (CD3+CD4-CD8-/ CD3+), T follicular helper cells % (CD3+CD4+CD8-CD185+/CD4+), T reg cells (CD4+CD8-CD25+CD127−/CD4+). Spearman’s correlation test was performed with all studied T cell subtypes in SPSS 21 package program. Main results and the role of chance The median percentage (range) of the studied T cell subtypes was: T helpers (51.7%, 12.1%÷91.45%), T killers (39.0%, 4.1%÷72.5%), DPT cells (1.2%, 0÷8.75), DNT cells (8.4%, 1.9%÷46.2%), Treg cells (4.6%, 1.9%÷12.7%), TFH cells (7.6%, 1.4%÷42.6%). To examine the association between the percentage of Treg cells and the other T cell subtypes, the Spearman’s Rho Correlation coefficient for non-paramentric data was used. No correlation was found between the quantity of Treg and T helpers, T killers, Total T cells, double-positive T cells (p > 0.05). In contrast, the percentage of Treg showed a significant positive correlation with the percentage of TFH (R = 0.36; p = 0.01), and a significant negative correlation with double-negative T cells (R= - 0.29; p = 0.04). Limitations, reasons for caution The main limitation of the study is that it was carried out only in a limited period of time during the pregnancy. Thus, it would be beneficial to compare the percentage of Treg cells with other T cell sub-types in the second and third trimester of pregnancy. Wider implications of the findings Our study demonstrated that Treg cells have stronger association with TFH cells than with other T cell subtypes. The strength of this quantitative relationship might be important for the normal progress of pregnancy, and it remains subject of further studies. Trial registration number not applicable

Interconversion between block coherence and multipartite entanglement in many-body systems

Coherence is intrinsically related to projective measurement. When the fixed projective measurement involves higher-rank projectors, the coherence resource is referred to as block coherence, which comes from the superposition of orthogonal subspaces. Here, we establish a set of quantitative relations for the interconversion between block coherence and multipartite entanglement under the framework of the block-incoherent operations. It is found that the converted multipartite entanglement is upper bounded by the initial block coherence of single-party system. Moreover, the generated multipartite entanglement can be transferred to its subsystems and restored to block coherence of the initial single-party system by means of local block-incoherent operations and classical communication. In addition, when only the coarse-grained quantum operations are accessible for the ancillary subsystems, we further demonstrate that a lossless resource interconversion is still realizable, and give a concrete example in three four-level systems. Our results provide a versatile approach to utilize different quantum resources in a cyclic fashion.

Exploiting game equilibrium mechanisms towards social trust-based group consensus reaching

In group decision making (GDM), the real or virtual moderator usually provides the suggestion and compensation based on consensus improvement for the decision maker (DM) to promote group consensus. In order to ensure DMs own interests, there are the game among DMs and the game between DM and moderator to effect the consensus reaching. In this case, we analyze the inherent game reasons and investigate the game-driven consensus model. Firstly, based on the subjective trust of social network and the evaluation consensus of DMs, and inspired by the idea of data envelopment analysis (DEA), this paper explores the quantitative relation between subjective trust and the DMs’ consensus to determine the DM’s weights. Then, under the compensation of consensus improvement, we formulate game strategy between DMs and the moderator to ensure the DM’s consensus, which impacts the cooperation behavior between DM and the moderator. Based on the game strategy, we further establish bi-level game consensus model and investigate Nash equilibrium of group consensus model. Finally, the experiments are used to illustrate the feasibility of the proposed method, and comparative analysis demonstrates its advantages.

BxC Toolkit: Generating Tailored Turbulent 3D Magnetic Fields

Turbulent states are ubiquitous in plasmas, and the understanding of turbulence is fundamental in modern astrophysics. Numerical simulations, which are the state-of-the-art approach to the study of turbulence, require substantial computing resources. Recently, attention shifted to methods for generating synthetic turbulent magnetic fields, affordably creating fields with parameter-controlled characteristic features of turbulence. In this context, the BxC toolkit was developed and validated against direct numerical simulations (DNSs) of isotropic turbulent magnetic fields. Here, we demonstrate novel extensions of BxC to generate realistic turbulent magnetic fields in a fast, controlled, geometric approach. First, we perform a parameter study to determine quantitative relations between the BxC input parameters and the desired characteristic features of the turbulent power spectrum, such as the extent of the inertial range, its spectral slope, and the injection and dissipation scale. Second, we introduce in the model a set of structured background magnetic fields, B 0, as a natural and more realistic extension to the purely isotropic turbulent fields. Third, we extend the model to include anisotropic turbulence properties in the generated fields. With all these extensions combined, our tool can quickly generate any desired structured magnetic field with controlled, anisotropic turbulent fluctuations, faster by orders of magnitude with respect to DNSs. These can be used, e.g., to provide initial conditions for DNSs or easily generate synthetic data for many astrophysical settings, all at otherwise unaffordable resolutions.