Correlation Effects Research Articles

Composition-driven Mott transition within SrTi 1−x V x O3

The last few decades has seen the rapid growth of interest in the bulk perovskite-type transition metal oxides SrVO3 and SrTiO3. The electronic configuration of these perovskites differs by one electron associated to the transition metal species which gives rise to the drastically different electronic properties. Therefore, it is natural to look into how the electronic structure transitions between these bulk structures by using doping. Measurements of the substitutional doped SrTi 1−x V x O3 shows an metal–insulator transition (MIT) as a function of doping. By using supercell density functional theory with dynamical mean field theory (DFT+DMFT), we show that the MIT is indeed the result of the combination of local electron correlation effects (Mott physics) within the t2g orbitals and the atomic site configuration of the transition metals which may indicate dependence on site disorder. SrTi 1−x V x O3 may be an ideal candidate for benchmarking cutting-edge Mott–Anderson models of real systems. We show that applying an effective external perturbation on SrTi 1−x V x O3 can switch the system between the insulating and metallic phase, meaning this is a bulk system with the potential use in Mott electronic devices.

Harmonic quantum cascade laser terahertz frequency combs enabled by multilayer graphene top-cavity scatters

Abstract Optical frequency comb synthesizers, operating in the harmonic regime, are metrological sources in which the emitted optical power is concentrated in a few modes, spaced by several multiples of the cavity free spectral range (FSR). This behavior reflects in a large correlation degree and, in principle, in an increased optical power per mode. In miniaturized quantum cascade lasers (QCLs), harmonic frequency combs (HFCs) are hence particularly attracting to explore quantum correlation effects between adjacent harmonic modes, enabled by the inherently large gain media third-order χ (3) Kerr nonlinearity, even if controlled generation of stable HFCs of predefined order, is typically demanding in such electrically pumped sources. Here, we demonstrate stable 2nd order and 3rd order HFC emission in terahertz frequency QCLs by respectively patterning an individual or a couple of equally spaced distributed multilayer graphene absorbers on the top metallic waveguides.

Triggering triboelectric nanogenerator antibacterial Activities: Effect of charge polarity and host material correlation

Triboelectric nanogenerators (TENGs) offer promising motion-driven energy harvesting for human–machine interactions, particularly in wearable healthcare and biomedical devices. However, direct skin contact demands addressing aggressive bacterial growth risks. The “triangle” interaction between bacteria, electrical stimulation, and host materials has been investigated comprehensively in the present study to facilitate appropriate self-antibacterial designs for TENGs. In so doing, it was revealed that the growth of negatively charged bacterial models (Escherichia coli and Staphylococcus aureus) was inhibited by induced positively charged substrates (Al or graphene oxide (GO)), regardless of the host material's composition due to the direct electrostatic interactions. Electron capture from the bacterial respiratory chain by the substrates leads to the interruption of the bacterial energy supply. In response to negative charges, however, an appreciable host-dependent antibacterial behaviour was observed, with Al showing a negligible bactericidal effect, while GO exhibited robust antibacterial properties. This effect was assigned to reactive oxygen species (ROS) generation, triggered by shuttling the negative charges to the oxygen functional groups in GO, suppressing bacterial growth efficaciously. The observed correlation between the electrostatic charge polarity and the material composition of the substrates (hosting the bacteria) highlights the superiority of ROS induction in the antibacterial properties of TENG. These findings pave the way for developing innovative approaches to control bacterial growth effectively and enhance the applicability of TENGs as advanced wearable devices with inherent antibacterial capabilities.

EXPLORING THE RELATIONSHIP BETWEEN PLANT HEIGHT AND YIELD-CONTRIBUTING ATTRIBUTES OF WHEAT IN DROUGHT CONDITIONS

Plant height is the most dynamic yield-affecting trait which has strong genetic and phenological associations with yield performance in wheat. The objective of the study was to explore the effect of plant height on spike yield by investigating the interrelationship between height and yield components of ninety wheat genotypes under a drought environment. Different statistical procedures including correlation, regression, path coefficient, principle component, biplot, and cluster analysis were performed to dissect the associative role of height and yield components in setting the yield potential of wheat plants. High positive correlation and direct effects are seen for spike yield from seed weight (r = 0.73) and seed number (r = 0.60) with a participatory contribution of 58% and 40%, respectively. But plant height is negatively associated with thousand seed weight (-0.22*) and spike yield (-0.15) in such a way that each additional unit (1cm) of height reduces 0.11 g thousand seed weight and 0.06 g spike yield due to negative regression. PC1 and PC2 associate height and yield components respectively and both types of traits moderately oppose each other for simultaneous improvement. Highly tall and short plants were observed with low yield potential under water-limited resources due to strong negative effects either on seed weight or number. An increase in height favors seed number but reduces enough seed weight to cause comparative losses. Intelligent allocation of plant resources to height or spike defines the plant yield potential. Plants with moderate height ranging from 74-83 cm were seen with the best yield potential among five different classes of height. Genotypes HM729, HM829, and HM644 belonged to this class and their better yield potential was due to the balance ratio of seed weight and number. This work would help direct our breeding programs for the improvement of the height-oriented yield potential of wheat.

Metal–insulator transition and G-type antiferromagnetism in CaNbO[formula omitted] perovskite: Insight from DFT+U study

In this work, we have investigated the ground state electronic and magnetic properties of CaNbO3 perovskite using the density functional theory, along with the Hubbard corrections. The study of structural, electronic, and magnetic properties was carried out using semi-empirical parameters. The structural properties reveal that Nb-O bond lengths are unequal in all directions, and ∠O-Nb-O bond angles are not equal to 90°, which makes NbO6 octahedra distorted. The electronic behavior of the compound, considering the strong correlation effect, shows a metal–insulator transition. The reason for this transition is found to be Jahn–Teller distortion. The stable magnetic state of the compound is obtained to be a G-type antiferromagnetic, using various U values.

An analysis of the role of college students' core self-evaluation in the relationship between extracurricular physical exercise and academic stress.

To explore the role of college students' core self-evaluation in the association between extracurricular physical exercise and academic stress, and to provide a reference and basis for effectively alleviating current college students' academic stress. A stratified cluster random sampling method was used to conduct an online survey using the China College Student Mental Health Screening Scale, the Core Self-Esteem Scale, and a self-developed questionnaire for 1,249 college students from 8 junior colleges in Jiangsu Province, China, in January 2023, and analyses were conducted using bivariate correlation and mediation effect tests. More than half of the students were worried about lagging behind other students in their studies and worrying about exams, as well as more than half of the students had <2 h of extracurricular physical exercise per week in terms of academic stress. Significant correlations were found between extracurricular physical exercise time and core self-evaluation (r = 0.225, p < 0.01), academic stress (r = -0.317, p < 0.01), and between core self-evaluation and academic stress (r =-0.371, p < 0.01). Extracurricular physical exercise had a negative predictive effect on academic stress (effect = -0.306, 95%CI: -0.361~-0.251) and partially through the mediating path of core self-evaluation, (effect = -0.067, 95%CI: -0.091~-0.046), with a mediating effect of 21.9%. Among them, the mediating effect of core self-evaluation was highest in "worrying about lagging behind other students in their studies" and "worrying about exams", which accounted for 24.4% and 24.3% respectively. Currently, college students have different degrees of academic stress; extracurricular physical exercise can reduce academic stress through direct effects, and also through the indirect effect of improving the level of core self-evaluation, and active extracurricular physical exercise has become an important way to promote students' physical and mental health.

Fiscal expenditure efficiency and green economic efficiency: evidence from Chinese cities

This study develops indicators for evaluating Green Economy Efficiency (GEE) and Fiscal Expenditure Efficiency (FEE) at the prefecture level and above within Chinese cities. Utilizing the super-efficiency SBM model and a three-stage DEA model, we empirically examine the influence of FEE on GEE. To address the issue of endogeneity arising from reverse causality between FEE and GEE, this research employs fiscal autonomy and officials’ tenure as instrumental variables for FEE. The key findings are summarized as follows: (1) GEE exhibits a fluctuating upward trend from 2006 to 2020, while FEE remains relatively stable overall. Notably, the GEE and FEE in the eastern region surpass those in the central and western regions. (2) A one percentage point increase in FEE corresponds to a substantial 7.597% rise in GEE, indicating a significant promotional effect, a result consistently upheld in robustness tests. Furthermore, factors such as urbanization level, economic development, education level, and industrial structure also contribute to urban green economic growth. (3) FEE primarily contributes to GEE through local economic growth, urban infrastructure development, and regional innovation levels. (4) The impact of FEE on GEE is more pronounced in developed cities, larger cities, those with high fiscal freedom, and highly urbanized cities. Based on these conclusions, policy recommendations are proposed: (1) contingent upon local circumstances, each municipal government should optimize its fiscal expenditure structure and enhance FEE based on its unique endowments; (2) make full use of spatial correlation and knowledge spillover effect to promote the coordinated growth of FEE and GEE; (3) improve urban infrastructure construction and encourage regional technological innovation.

Correlation Between Gaze Behaviors and Social Communication Skills of Young Autistic Children: A Meta-Analysis of Eye-Tracking Studies.

This meta-analysis examined correlations between eye-tracking measures of gaze behaviors manifested during dynamic salient social stimuli and behavioral assessment measures of social communication skills of young autistic children. We employed a multilevel model with random effects to perform three separate meta-analyses for correlation between social communication skills and (a) all gaze behaviors, (b) gaze duration, and (c) gaze transition. Subsequently, we performed meta-regression to assess the role of four moderators, including age, continuum of naturalness of stimuli, gaze metric, and area of interest, on correlation effect sizes that were heterogeneous at the population level. A total of 111 correlation coefficients from 17 studies for 1132 young autistic children or children with high-likelihood for autism (Mage range = 6-95months) were included in this meta-analysis. The correlation effect sizes for all three meta-analyses were significant, supporting the relation between improved gaze behaviors and better social communication skills. In addition, age, gaze metric, and area of interest were significant moderators. This suggests the importance of identifying meaningful gaze behaviors related to social communication skills and the increasingly influential role of gaze behaviors in shaping social communication skills as young autistic children progress through the early childhood stage. The continuum of naturalness of stimuli, however, was revealed to trend towards having a significant moderating effect. Lastly, it is important to note the evidence of potential publication bias. Our findings are discussed in the context of early identification and intervention and unraveling the complex nature of autism.

How does personality affect perception of advertising messages? The Big Five model and advertising responses: a meta-analysis

An attempt to identify relationships between the Big Five personality traits and responses to advertising was made by meta-analyzing results of 15 studies (308 correlations). Variables of brand familiarity, types of advertising appeals and types of responses were used as moderators of advertising responses. The overall correlation effect between personality traits and advertising responses was significant, with Agreeableness, Extraversion and Openness responsible for this effect. Moderating effects of brand familiarity showed strong relationships between Extraversion and advertising responses for unfamiliar brands, whereas Agreeableness, Conscientiousness, Openness for familiar ones. Moderating effect of advertising appeals was found for value-expressive appeals but not for utilitarian ones. Moderations of a type of advertising response showed that the relationship between advertising response and personality is mostly shaped by AAd and ABrand. Since effectiveness of personality-fitted advertising is of growing interest to both researchers and practitioners, this meta-analysis offers preliminary guidelines for future research in the area.

Discovery of controllable high Chern number quantum anomalous Hall state in tetragonal lattice FeSIn

Quantum anomalous Hall (QAH) insulators have excellent properties driven by fancy topological physics, but their practical application is greatly hindered by the observed temperature of liquid nitrogen, and the QAH insulator with high Chern number is conducive to spintronic devices with lower energy consumption. Here, we find that monolayer FeSIn is a good candidate for realizing the QAH phase; it exhibits a high magnetic transition temperature of 221 K and tunable C = ±2 with respect to magnetization orientation in the y–z plane. After the application of biaxial strain, the magnetic axis shifts from the x–y plane to the z direction, and the effect of the high C and ferromagnetic ground state on the stress is robust. Also, the effect of correlation U on C has been examined. These properties are rooted in the large size of the Fe atom that contributes to ferromagnetic kinetic exchange with neighboring Fe atoms. These findings demonstrate monolayer FeSIn to be a major template for probing novel QAH devices at higher temperatures.

Direct Visualization of Confinement and Many‐Body Correlation Effects in 2D Spectroscopy of Quantum Dots

AbstractThe size tunable color of colloidal semiconductor quantum dots (QDs) is probably the most elegant illustration of the quantum confinement effect. As explained by the simple “particle‐in‐a‐box” model, the transition energies between the levels increase when the “box” becomes smaller. To investigate quantum confinement effects, typically a well‐defined narrow size distribution of the nanoparticles is needed. In this contribution, how coherent electronic two‐dimensional spectroscopy (2DES) can directly visualize the quantum size effect in a sample with broad size distribution of QDs is demonstrated. The method is based on two features of the 2DES – the ability to resolve inhomogeneous broadening and the capability to reveal correlations between the states. In QD samples, inhomogeneous spectral broadening is mainly caused by the size distribution and leads to elongated diagonal peaks of the spectra. Since the cross peaks correlate the energies of two states, they allow drawing conclusions about the size dependence of the corresponding states. It is also found that the biexciton binding energy changes between 3 and 8 meV with the QD size. Remarkably, the size dependence is non‐monotonic with a clear minimum.

The effects of higher-order human values and conspiracy beliefs on COVID-19-related behavior in Germany

Abstract Aim This article simultaneously examines the influence of Schwartz’ higher-order human values (self-transcendence, openness to change, self-enhancement, and conservation) and conspiracy beliefs on four COVID-19-related dependent variables. Subject and methods Using path analysis with large-scale panel data from Germany (N = 4382), we tested if the correlational effects of higher-order values as independent variables on the perceived threat of the infection event, evaluation of government measures, number of self-initiated measures, and trust toward individuals and institutions involved as dependent variables could be mediated by conspiracy beliefs. Results We found evidence of a significant influence of all four higher-order values on the strength of conspiracy beliefs. In addition, we detected effects of higher-order values and conspiracy beliefs on all four COVID-19-related measures. Self-transcendence with consistently positive and openness to change with consistently negative total, direct, and indirect effects provided the most evident results. The respondents’ country of origin and residence in East or West Germany affected all four COVID-19-related variables. Conclusion This article has shown that belief in conspiracy narratives reveals associations of higher-order values with all four COVID-19-related measures that would not have been apparent without this mediator. In doing so, it contributes to the understanding of how pandemic mitigation measures are implemented differently. The results of this study can improve the ability to develop and enforce policies to increase the acceptance of scientifically accepted efforts in better governance.

Comparison of state-of-knowledge correlation effect associated with lognormal, beta, and gamma uncertainty distributions

In the probabilistic safety assessment (PSA) of nuclear power plants, the state-of-knowledge correlation (SOKC) is required to be considered when estimating the risk measures and their uncertainties. Specifically, the SOKC must be taken into account when the failure data for similar components are aggregated to produce the failure rate or failure probability for the components and their uncertainty distributions. The objective of this study is to mathematically prove what has been numerically observed in the existing studies: The SOKC effect is more significant if the uncertainty is modeled with a lognormal distribution than when it is modeled with a gamma or beta distribution when the parameters of the two distributions are estimated from the same failure data by using the method of moments. An example based on the frequency calculation for interfacing system loss of coolant accidents is provided to demonstrate the proof. The mathematical proof provides a relationship between the raw moments of lognormal, gamma, and beta distributions, which is expected to be valuable in probability and statistics theories.

A Quantum Chemistry Approach to Linear Vibro-Polaritonic Infrared Spectra with Perturbative Electron-Photon Correlation.

In the vibrational strong coupling (VSC) regime, molecular vibrations and resonant low-frequency cavity modes form light-matter hybrid states, vibrational polaritons, with characteristic infrared (IR) spectroscopic signatures. Here, we introduce a molecular quantum chemistry-based computational scheme for linear IR spectra of vibrational polaritons in polyatomic molecules, which perturbatively accounts for nonresonant electron-photon interactions under VSC. Specifically, we formulate a cavity Born-Oppenheimer perturbation theory (CBO-PT) linear response approach, which provides an approximate but systematic description of such electron-photon correlation effects in VSC scenarios while relying on molecular ab initio quantum chemistry methods. We identify relevant electron-photon correlation effects at the second order of CBO-PT, which manifest as static polarizability-dependent Hessian corrections and an emerging polarizability-dependent cavity intensity component providing access to transmission spectra commonly measured in vibro-polaritonic chemistry. Illustratively, we address electron-photon correlation effects perturbatively in IR spectra of CO2 and Fe(CO)5 vibro-polaritonic models in sound agreement with nonperturbative CBO linear response theory.

Cognitive Illusion, Lucid Dreaming, and the Psychology of Metaphor in Tibetan Buddhist Dzogchen Contemplative Practices

A classic set of eight similes of illusion (sgyu ma’i dpe brgyad) are employed recurrently throughout Indian and Tibetan Buddhist literature to illustrate the operations of cognition, its correlative perceptions, and experiences that emerge. To illustrate a Buddhist psychology of metaphor, the fourteenth century Tibetan scholar and synthesizer of the Dzogchen (rdzogs chen) or Great Perfection system, Longchen Rabjam Drimé Ödzer (1308-1363), composed his poetic text, Being at Ease with Illusion. This work on illusion is the third volume in Longchenpa’s Trilogy of Being at Ease (Ngal gso skor gsum) in which he presents a series of Dzogchen instructions on how to settle totally at ease. To complement each volume in his trilogy, Longchenpa composed auxiliary contemplative guidance instructions on their meaning (don khrid). This article contextualizes Longchenpa’s meditation manual on Being at Ease with Illusion, a translation of which is included in the appendix. Special attention is given to Dzogchen practices of lucid dreaming and working with cognitive illusions to spotlight underlying contemplative dynamics and correlative psychological effects. To analogically map these Tibetan language instructions in translation, this article interprets Buddhist psychological understandings of cognitive and perceptual processes in dialogue with current theories in the cognitive sciences.

New-Generation Electron-Propagator Methods for Molecular Electron-Binding Energies.

A new generation of electron-propagator methods for the calculation of electron binding energies has surpassed its antecedents with respect to accuracy, efficiency, and interpretability. No adjustable parameters are introduced in these fully ab initio procedures. Numerical tests versus several databases of valence, vertical electron binding energies of closed-shell molecules and atoms have been performed. Easily interpreted self-energy approximations with cubic arithmetic scaling produce mean absolute errors (MAEs) of 0.2 and 0.3 eV for electron detachments and attachments, respectively. The most accurate explicitly renormalized methods with fifth-power arithmetic scaling yield MAEs below 0.1 eV for detachments and attachments. Approximate renormalization leads to more efficient fifth-power alternatives for electron detachments that achieve similar accuracy with fewer bottleneck operations. Composite protocols generate excellent predictions versus highly accurate basis-extrapolated standards and experiments. The validity of the diagonal self-energy approximation and the accuracy of the approximate renormalizations are confirmed. The success of these perturbative methods based on canonical Hartree-Fock orbitals rests on a Hermitized, intermediately normalized superoperator metric. The results of all of the new-generation calculations may be analyzed in terms of final-state orbital relaxation and differential correlation effects.

Family Culture's Impact on Chinese Students' Employment Intention

In 2022, a record 4.57 million individuals in China sat for the postgraduate entrance exam, yet only 1.1 million were admitted to graduate programs. Amidst this intense local competition, the allure of studying overseas has grown among Chinese families, with Thailand emerging as a favored destination due to its affordability and conducive Chinese cultural environment. This research aims to explore how family cultural capital influences the career aspirations of Chinese students in Thailand, focusing particularly on how parental educational expectations act as a mediator in this process. Utilizing a survey method, the study gathered 344 valid responses for analysis. Through descriptive statistics, correlation, and mediation effect analyses, it was found that in Thailand, the cultural capital of a Chinese student's family significantly boosts their career intentions. Moreover, such cultural capital profoundly affects parental expectations regarding education, which in turn positively influences students' career plans. The study highlights the mediating role of parental educational expectations in linking family cultural capital with students' job aspirations. The findings advocate for the importance of nurturing family cultural capital and reducing disparities in cultural capital among families. It recommends moderating parental expectations to lessen the academic load on students, based on the insights gained from the research.

AST3DRNet: Attention-Based Spatio-Temporal 3D Residual Neural Networks for Traffic Congestion Prediction.

Traffic congestion prediction has become an indispensable component of an intelligent transport system. However, one limitation of the existing methods is that they treat the effects of spatio-temporal correlations on traffic prediction as invariable during modeling spatio-temporal features, which results in inadequate modeling. In this paper, we propose an attention-based spatio-temporal 3D residual neural network, named AST3DRNet, to directly forecast the congestion levels of road networks in a city. AST3DRNet combines a 3D residual network and a self-attention mechanism together to efficiently model the spatial and temporal information of traffic congestion data. Specifically, by stacking 3D residual units and 3D convolution, we proposed a 3D convolution module that can simultaneously capture various spatio-temporal correlations. Furthermore, a novel spatio-temporal attention module is proposed to explicitly model the different contributions of spatio-temporal correlations in both spatial and temporal dimensions through the self-attention mechanism. Extensive experiments are conducted on a real-world traffic congestion dataset in Kunming, and the results demonstrate that AST3DRNet outperforms the baselines in short-term (5/10/15 min) traffic congestion predictions with an average accuracy improvement of 59.05%, 64.69%, and 48.22%, respectively.

On the study of electrical transport properties of some liquid metals by pseudopotential method

ABSTRACT Our recently evolved pseudopotential is used to study the electrical transport properties such as electrical resistivity ( ρ ), thermal conductivity ( σ ) and thermoelectric power ( TEP ) of some monovalent (Li, Na, K, Rb, Cs), divalent (Mg, Zn, Ca) and polyvalent (Al, Ga, In, Pb, Sn, Bi, Sb) liquid metals. The model potential theory in conjunction with Ziman, mean free path, t-matrix, and Kubo models are implemented in the above-mentioned work for the first time. The Taylor’s local field correction function (T) is taken for observing the exchange and correlation effect with one component plasma (OCP) structure factor method of liquid metals with Hartree dielectric function (H). The presently computed findings are extremely comparable with available data, either theoretical or experimental results that exist in the literature.

Excited States by Coupling Piris Natural Orbital Functionals with the Extended Random-Phase Approximation.

In this work, we explore the use of Piris natural orbital functionals (PNOFs) to calculate excited-state energies by coupling their reconstructed second-order reduced density matrix with the extended random-phase approximation (ERPA). We have named the general method PNOF-ERPA, and specific approaches are referred to as PNOF-ERPA0, PNOF-ERPA1, and PNOF-ERPA2, according to the way the excitation operator is built. The implementation has been tested in the first excited states of H2, HeH+, LiH, Li2, and N2 showing good results compared to the configuration interaction (CI) method. As expected, an increase in accuracy is observed on going from ERPA0 to ERPA1 and ERPA2. We also studied the effect of electron correlation included by PNOF5, PNOF7, and the recently proposed global NOF (GNOF) on the predicted excited states. PNOF5 appears to be good and may even provide better results in very small systems, but including more electron correlation becomes important as the system size increases, where GNOF achieves better results. Overall, the extension of PNOF to excited states has been successful, making it a promising method for further applications.