Range Correlations Research Articles

Antiferromagnetic Ordering and Uncoupled Spins in CaFe2O4 Thin Films Probed by Spin Hall Magnetoresistance

AbstractCaFe2O4 is a uniaxial antiferromagnet displaying two coexisting magnetic orderings, A and B, characterized by ↑↑↓↓ and ↑↓↑↓ spin modulation, respectively, and the emergence of a net magnetization in a limited temperature range, which is not yet understood. The spin Hall magnetoresistance (SMR) is probed at the interface between Pt and CaFe2O4 and the crystallographic domain structure of thin film samples is exploited to perform single‐ and multi‐domain scale measurements. The SMR response, upon rotating the magnetic field along three orthogonal planes, shows little effect of the strong magnetocrystalline and shape anisotropies. Together with the response to a varying magnetic field strength, the modulations in the SMR signal allow to extract two contributions: one corresponds to the long‐range antiferromagnetic ordering, supporting a single ground state scenario; while the second contribution originates from uncompensated, non‐interacting spins. These are expected to exist at the antiphase boundaries between antiferromagnetic domains. Here, it is shown that these are also uncoupled from the antiferromagnetic ordering. Nonetheless, the long range correlations that emerge in the proximity of the critical antiferromagnetic transition can give rise to ordering of the uncompensated spins and be responsible for the net magnetization observed in this antiferromagnet.

Inter-event Times Statistic in Stationary Processes: Nonlinear ARMA Modeling of Wind Speed Time Series

The random sequence of inter-event times of a level-crossing is a statistical tool that can be used to investigate time series from complex phenomena. Typical features of observed series as the skewed distribution and long range correlations are modeled using non linear transformations applied to Gaussian ARMA processes. We investigate the distribution of the inter-event times of the level-crossing events in ARMA processes in function of the probability corresponding to the level. For Gaussian ARMA processes we establish a representation of this indicator, prove its symmetry and that it is invariant with respect to the application of a non linear monotonic transformation. Using simulated series we provide evidence that the symmetry disappears if a non monotonic transformation is applied to an ARMA process. We estimate this indicator in wind speed time series obtained from three different databases. Data analysis provides evidence that the indicator is non symmetric, suggesting that only highly non linear transformations of ARMA processes can be used in modeling. We discuss the possible use of the inter-event times in the prediction task.

Repeatability and Reproducibility of Computed Tomography Radiomics for Pulmonary Nodules: A Multicenter Phantom Study.

BackgroundRadiomics can yield minable information from medical images, which can facilitate computer-aided diagnosis. However, the lack of repeatability and reproducibility of radiomic features (RFs) may hinder their generalizability in clinical applications.ObjectivesThe aims of this study were to explore 3 main sources of variability in RFs, investigate their influencing magnitudes and patterns, and identify a subset of robust RFs for further studies.Materials and MethodsA chest phantom with nodules was scanned with different computed tomography (CT) scanners repeatedly with varying acquisition and reconstruction parameters (April-May 2019) to evaluate 3 sources of variability: test-retest, inter-CT, and intra-CT protocol variability. The robustness of the RFs was measured using the concordance correlation coefficient, dynamic range, and intraclass correlation coefficient (ICC). The influencing magnitudes and patterns were analyzed using the Friedman test and Spearman rank correlation coefficient. Stable and informative RFs were selected, and their redundancy was eliminated using hierarchical clustering. Clinical validation was also performed to verify the clinical effectiveness and potential enhancement of the generalizability of radiomics research.ResultsA total of 1295 RFs that showed all 3 sources of variability were included. The reconstruction kernel and the iteration level showed the greatest (ICC, 0.35 ± 0.31) and the least (ICC, 0.63 ± 0.27) influence on magnitudes. The different sources of variability showed relatively consistent patterns of influence (false discovery rate <0.001). Finally, we obtained a subset of 19 stable, informative, and nonredundant RFs under all 3 sources of variability. These RFs exhibited clinical effectiveness and showed better prediction performance than unstable RFs in the validation dataset (P = 0.017, Delong test).ConclusionsThe stability of RFs was affected to different degrees by test-retest and differences in CT manufacturers and models and CT acquisition and reconstruction parameters, but the influences of these factors showed relatively consistent patterns. We also obtained a subset of 19 stable, informative, and nonredundant RFs that should be preferably used to enhance the generalizability of further radiomics research.

Sensitivity of Remotely Sensed Vegetation to Hydrologic Predictors across the Colorado River Basin, 2001–2019

AbstractIn water‐limited regions, it is important to understand the response of vegetation to hydrologic predictors for fire management and water resource planning. We present a novel spatially distributed analysis of ecohydrological interactions in the semi‐arid Colorado River Basin (CRB) over 18 years, 2001–2019. The hydrologic predictors used include precipitation from the Integrated Multi‐satellitE Retrievals for GPM, 0‐ to 10‐cm‐depth surface soil moisture (SSM) estimations from the National Land Data Assimilation System, and newly available 0‐ to 40‐cm depth Soil MERGE root zone soil moisture (RZSM) estimations. These are evaluated using time‐lagged correlations with the Enhanced Vegetation Index (EVI) from MODerate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that EVI response is strongest and most immediate to the hydrologic predictors in the hot and dry southwestern CRB, with lag times of 0–32 days. RZSM was expected to provide the best predictor of EVI, but we found SSM to be a superior predictor of EVI with interquartile range correlations of 0.20–0.37 across the CRB. RZSM had slightly lower interquartile range correlations of 0.15–0.35, and precipitation was the least effective predictor of EVI with interquartile range correlations of 0.11–0.26. Plotting these cross‐correlations provides a spatially explicit overview of temporal dependence between SSM, RZSM, precipitation, and EVI with publicly available datasets.

Standard reference values of the upper body posture in healthy male adults aged between 31 and 40 years in Germany-an observational study

BackgroundIn order to classify and analyze the parameters of upper body posture, a baseline in the form of standard values is demanded. To this date, standard values have only been published for healthy men aged 18–35 and 41–50 years. Data for male adults aged between 31 and 40 years are lacking.MethodsThe postural parameters of 101 symptom-free male volunteers aged 31–40 (35.58 ± 2.88) years were studied. The mean height of the men was 179.89 ± 7.38 cm, with a mean body weight of 86.36 ± 11.58 kg and an average BMI of 26.70 ± 3.35 kg/m2. By means of video rasterstereography, a 3-dimensional scan of the upper back surface was measured in a habitual standing position. The means or medians, confidence interval, tolerance range, and group comparisons and correlations of BMI and physical activity were calculated for all parameters.ResultsThe habitual standing position was found to be almost symmetrical and the axis aligned in the spine, pelvis, and shoulder region, while the spine position was marginally inclined ventrally. The kyphosis angle of the thoracic spine was greater than the lordosis angle of the lumbar spine. All deviations fell under the measurement error margin of 1 mm/1°. The greater the BMI, the greater was the pelvic and scapular distance. The lower the BMI, the further caudally positioned was the right shoulder. The pelvic and scapular distances were also lower with the increasing athleticism of the participants.ConclusionThe upper body posture of men between the ages of 31 and 40 years was found to be almost symmetrical and axis-conforming, with the kyphosis angle, pelvic distance, and shoulder distance enlarging with increasing BMI. Consequently, postural parameters presented in this survey allow for comparisons with other studies, as well as the evaluation of clinical diagnostics and applications.

Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean

The variance κ1 of the natural time analysis of earthquake catalogs was proposed in 2005 as an order parameter for seismicity, whose fluctuations proved, in 2011, to be minimized a few months before the strongest mainshock when studying the earthquakes in a given area. After the introduction of earthquake networks based on similar activity patterns, in 2012, the study of their higher order cores revealed, in 2019, the selection of appropriate areas in which the precursory minima βmin of the fluctuations β of the seismicity order parameter κ1 could be observed up to six months before all strong earthquakes above a certain threshold. The eastern Mediterranean region was studied in 2019, where all earthquakes of magnitude M≥7.1 were found to be preceded by βmin without any false alarm. Combining these results with the method of nowcasting earthquakes, introduced in 2016, for seismic risk estimation, here, we show that the epicenter of an impending strong earthquake can be estimated. This is achieved by employing—at the time of observing the βmin—nowcasting earthquakes in a square lattice grid in the study area and by averaging, self-consistently, the results obtained for the earthquake potential score. This is understood in the following context: The minimum βmin is ascertained to almost coincide with the onset of Seismic Electric Signals activity, which is accompanied by the development of long range correlations between earthquake magnitudes in the area that is a candidate for a mainshock.

Planar triangular S=3/2 magnet AgCrSe2 : Magnetic frustration, short range correlations, and field-tuned anisotropic cycloidal magnetic order

Single crystals of the hexagonal triangular lattice compound AgCrSe2 have been grown by chemical vapor transport. The crystals have been carefully characterized and studied by magnetic susceptibility, magnetization, specific heat, and thermal expansion. In addition, we used Cr-electron spin resonance and neutron diffraction to probe the Cr 3d3 magnetism microscopically. To obtain the electronic density of states, we employed x-ray absorption and resonant photoemission spectroscopy in combination with density functional theory calculations. Our studies evidence an anisotropic magnetic order below TN=32K. Susceptibility data in small fields of about 1 T reveal an antiferromagnetic (AFM) type of order for H⊥c, whereas for H∥c the data are reminiscent of a field-induced ferromagnetic (FM) structure. At low temperatures and for H⊥c, the field-dependent magnetization and AC susceptibility data evidence a metamagnetic transition at H+=5T, which is absent for H∥c. We assign this to a transition from a planar cycloidal spin structure at low fields to a planar fanlike arrangement above H+. A fully ferromagnetically polarized state is obtained above the saturation field of H⊥S=23.7T at 2 K with a magnetization of Ms=2.8μB/Cr. For H∥c, M(H) monotonically increases and saturates at the same Ms value at H∥S=25.1T at 4.2 K. Above TN, the magnetic susceptibility and specific heat indicate signatures of two dimensional (2D) frustration related to the presence of planar ferromagnetic and antiferromagnetic exchange interactions. We found a pronounced nearly isotropic maximum in both properties at about T*=45K, which is a clear fingerprint of short range correlations and emergent spin fluctuations. Calculations based on a planar 2D Heisenberg model support our experimental findings and suggest a predominant FM exchange among nearest and AFM exchange among third-nearest neighbors. Only a minor contribution might be assigned to the antisymmetric Dzyaloshinskii-Moriya interaction possibly related to the noncentrosymmetric polar space group R3m. Due to these competing interactions, the magnetism in AgCrSe2, in contrast to the oxygen-based delafossites, can be tuned by relatively small, experimentally accessible magnetic fields, allowing us to establish the complete anisotropic magnetic H-T phase diagram in detail.9 MoreReceived 4 August 2021Revised 3 September 2021Accepted 20 September 2021DOI:https://doi.org/10.1103/PhysRevB.104.134410Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasFrustrated magnetismMagnetic susceptibilityThermal expansionTechniquesElectron spin resonanceNeutron diffractionPhotoemission spectroscopySpecific heat measurementsCondensed Matter & Materials Physics

Development of an environmental contextual factor item set relevant to global functioning and health in patients with axial spondyloarthritis.

To describe the development of an Environmental contextual factors (EF) Item Set (EFIS) accompanying the disease specific Assessment of SpondyloArthritis international Society Health Index (ASAS HI). First, a candidate item pool was developed by linking items from existing questionnaires to 13 EF previously selected for the International Classification of Functioning, Disability and Health (ICF) /ASAS Core Set. Second, using data from two international surveys, which contained the EF item pool as well as the items from the ASAS HI, the number of EF items was reduced based on the correlation between the item and the ASAS HI sum score combined with expert opinion. Third, the final English EFIS was translated into 15 languages and cross-culturally validated. The initial item pool contained 53 EF addressing four ICF EF chapters: products and technology (e1), support and relationship (e3), attitudes (e4) and health services (e5). Based on 1754 responses of axial spondyloarthritis patients in an international survey, 44 of 53 initial items were removed based on low correlations to the ASAS HI or redundancy combined with expert opinion. Nine items of the initial item pool (range correlation 0.21-0.49) form the final EFIS. The EFIS was translated into 15 languages and field tested in 24 countries. An EFIS is available complementing the ASAS HI and helps to interpret the ASAS HI results by gaining an understanding of the interaction between a health condition and contextual factors. The EFIS emphasizes the importance of support and relationships, as well as attitudes of the patient and health services in relation to self-reported health.

An Application of the Information Entropy to Nuclei

Shannon's information entropies in position- and momentum-space and their sum $S$ are calculated for various $s$-$p$ and $s$-$d$ shell nuclei using a correlated one-body density matrix depending on the harmonic oscillator size $b_0$ and the short range correlation parameter $y$ which originates from a Jastrow correlation function. It is found that the information entropy sum for a nucleus depends only on the correlation parameter $y$ through the simple relation $S= s_{0A} + s_{1A} y^{-\lambda_{sA}}$, where $s_{0A}$, $s_{1A}$ and $\lambda_{sA}$ depend on the mass number $A$. Finally, we propose a method to determine the correlation parameter from the above property of $S$ as well as the linear dependence of $S$ on the logarithm of the number of nucleons.

Nuclear effects in neutrino-nucleus DIS and a probe for short-range correlations

We investigate charged-current neutrino-nucleus deep inelastic scattering with particular interests in relationship of short range correlation (SRC) and EMC effect. The structure functions $F^A_2(x,Q^2)$, $x F^A_3(x,Q^2)$ and ratios of differential cross sections are presented where the nuclei $A$ are chosen to be carbon, iron and lead. We propose a kind of universal modification functions which would provide a nontrivial test of SRC universality on the platform of neutrino-nucleus scattering and improve our understanding of nucleon structure substantially.

12C(e,e'pN) measurements of short range correlations in the tensor-to-scalar interaction transition region

High-momentum configurations of nucleon pairs at short-distance are probed using measurements of the 12C(e,e′p) and 12C(e,e′pN) reactions (where N is either n or p), at high-Q2 and xB>1.1. The data span a missing-momentum range of 300–1000 MeV/c and are predominantly sensitive to the transition region of the strong nuclear interaction from a Tensor to Scalar interaction. The data are well reproduced by theoretical calculations using the Generalized Contact Formalism with both chiral and phenomenological nucleon-nucleon (NN) interaction models. This agreement suggests that the measured high missing-momentum protons up to 1000 MeV/c predominantly belong to short-ranged correlated (SRC) pairs. The measured 12C(e,e′pN) / 12C(e,e′p) and 12C(e,e′pp) / 12C(e,e′pn) cross-section ratios are consistent with a decrease in the fraction of proton-neutron SRC pairs and increase in the fraction of proton-proton SRC pairs with increasing missing momentum. This confirms the transition from an isospin-dependent tensor NN interaction at ∼400 MeV/c to an isospin-independent scalar interaction at high-momentum around ∼800 MeV/c as predicted by theoretical calculation.

Fano resonance and relaxor behavior in Pr doped SrTiO3: A Raman spectroscopic investigation

The phenomenon of relaxor ferroelectrics is studied through detailed Raman spectroscopy on polycrystalline Sr1-xPrxTiO3 (x = 0.01–0.17) samples. The polar mode was observed up to very high temperature ~1000 K indicating presence of dipoles well above the characteristic relaxor temperatures and they develop a short range correlation at 505 K leading to formation of PNRs. Below 505 K, the TO2 polar mode anomalously soften along with Fano resonance and changes in the octahedral tilt angle. This establishes growth of local polar order associated with local structural phase transition at T ~505 K. The local TiO6 octahedral tilt scales with the intensity of the polar mode and hence can be used as an order parameter for relaxor transition. It is shown that the paraelectric to relaxor ferroelectric phase transition in this compound is random polarizability instability driven phenomenon which has been correlated with the local octahedral tilt angle.

Long range correlations and slow time scales in a boundary driven granular model

We consider a velocity field with linear viscous interactions defined on a one dimensional lattice. Brownian baths with different parameters can be coupled to the boundary sites and to the bulk sites, determining different kinds of non-equilibrium steady states or free-cooling dynamics. Analytical results for spatial and temporal correlations are provided by analytical diagonalisation of the system’s equations in the infinite size limit. We demonstrate that spatial correlations are scale-free and time-scales become exceedingly long when the system is driven only at the boundaries. On the contrary, in the case a bath is coupled to the bulk sites too, an exponential correlation decay is found with a finite characteristic length. This is also true in the free cooling regime, but in this case the correlation length grows diffusively in time. We discuss the crucial role of boundary driving for long-range correlations and slow time-scales, proposing an analogy between this simplified dynamical model and dense vibro-fluidized granular materials. Several generalizations and connections with the statistical physics of active matter are also suggested.

The Impact of Reflectivity Gradients on the Performance of Range-Oversampling Processing

AbstractRange-oversampling processing is a technique that can be used to lower the variance of radar-variable estimates, reduce radar update times, or a mixture of both. There are two main assumptions for using range-oversampling processing: accurate knowledge of the range correlation and uniform reflectivity in the radar resolution volume. The first assumption has been addressed in previous research; this work focuses on the uniform reflectivity assumption. Earlier research shows that significant reflectivity gradients can occur in storms; we utilized those results to develop realistic simulations of radar returns that include effects of reflectivity gradients in range. An important consideration when using range-oversampling processing is the resulting change in the range weighting function. The range weighting function can change for different types of range-oversampling processing and some techniques, such as adaptive pseudowhitening, can lead to different range weighting functions at each range gate. To quantify the possible effects of differing range weighting functions in the presence of reflectivity gradients, we developed simulations to examine varying types of range-oversampling processing with two receiver filters: a matched receiver filter and a wider-bandwidth receiver filter (as recommended for use with range oversampling). Simulation results show that differences in range weighting functions are the only contributor to differences in radar reflectivity measurements. Results from real weather data demonstrate that the reflectivity gradients that occur in typical severe storms do not cause significant changes in reflectivity measurements, and the benefits from range-oversampling processing outweigh the possible isolated effects from large reflectivity gradients.

The [formula omitted]-exponentials do not maximize the Rényi entropy

It is generally assumed that the Rényi entropy is maximized by the q-exponentials and is hence useful to construct a generalized statistical mechanics. However, to the best of our knowledge, this assumption has never been explicitly checked. In this work, we consider the Rényi entropy with the linear and escort mean value constraints and check whether it is indeed maximized by q-exponentials. We show, both theoretically and numerically, that the Rényi entropy yields erroneous inferences concerning the optimum distributions of the q-exponential form and moreover exhibits high estimation errors in the regime of long range correlations. Finally, we note that the Shannon entropy successfully detects the power law distributions when the logarithmic mean value constraint is used.

A near analytic solution of a stochastic immune response model considering variability in virus and T-cell dynamics.

Biological processes at the cellular level are stochastic in nature, and the immune response system is no different. Therefore, models that attempt to explain this system need to also incorporate noise or fluctuations that can account for the observed variability. In this work, a stochastic model of the immune response system is presented in terms of the dynamics of T cells and virus particles. Making use of the Green's function and the Wilemski-Fixman approximation, this model is then solved to obtain the analytical expression for the joint probability density function of these variables in the early and late stages of infection. This is then also used to calculate the average level of virus particles in the system. Upon comparing the theoretically predicted average virus levels to those of COVID-19 patients, it is hypothesized that the long-lived dynamics that are characteristics of such viral infections are due to the long range correlations in the temporal fluctuations of the virions. This model, therefore, provides an insight into the effects of noise on viral dynamics.

Pruning the Pilots: Deep Learning-Based Pilot Design and Channel Estimation for MIMO-OFDM Systems

With the large number of antennas and subcarriers the overhead due to pilot transmission for channel estimation can be prohibitive in wideband massive multiple-input multiple-output (MIMO) systems. This can degrade the overall spectral efficiency significantly, and as a result, curtail the potential benefits of massive MIMO. In this paper, we propose a neural network (NN)-based joint pilot design and downlink channel estimation scheme for frequency division duplex (FDD) MIMO orthogonal frequency division multiplex (OFDM) systems. The proposed NN architecture uses fully connected layers for frequency-aware pilot design, and outperforms linear minimum mean square error (LMMSE) estimation by exploiting inherent correlations in MIMO channel matrices utilizing convolutional NN layers. Our proposed NN architecture uses a non-local attention module to learn longer range correlations in the channel matrix to further improve the channel estimation performance.We also propose an effective pilot reduction technique by gradually pruning less significant neurons from the dense NN layers during training. This constitutes a novel application of NN pruning to reduce the pilot transmission overhead. Our pruning-based pilot reduction technique reduces the overhead by allocating pilots across subcarriers non-uniformly and exploiting the inter-frequency and inter-antenna correlations in the channel matrix efficiently through convolutional layers and attention module.

Effect of the alkyl chain length on the non-ideality and the microstructure of alcohol binary mixtures

In this study the microstructure of alcohol binary mixtures (toluene and cyclohexane) is investigated from molecular dynamics simulations. In case of cyclohexane mixtures, we show that the strong deviation from the ideality is the result of the formation of nanophases of alcohol molecules gathered in aggregates from hydrogen bonds leading to the spatial heterogeneity. Nanophases disappear as the alkyl chain size increases because the hydrophobic interactions counteracts the hydrogen bonds ones. The aggregates of short alcohol are found uncorrelated at the long range correlations which is related to an absence of the prepeak at low Q in the total structure factor. From toluene similar trends are observed with a lesser extend given the favorable π-OH interactions.

Exploring collective phenomena at the electron-ion collider

Based on rare fluctuations in strong interactions, we argue that there is a strong physical resemblance between the high multiplicity events in photo-nuclear collisions and those in $pA$ collisions, in which interesting long range collective phenomena are discovered. This indicates that the collectivity can also be studied in certain kinematic regions of the upcoming electron-ion collider (EIC), where the incoming virtual photon has a sufficiently long lifetime. Using a model in the color glass condensate formalism, we first show that the initial state interactions can explain the recent ATLAS azimuthal correlation results measured in the photo-nuclear collisions, and then we provide quantitative predictions for the long range correlations in $eA$ collisions in the EIC regime. With the unprecedented precision and the ability to change size of the collisional system, the high luminosity EIC will open a new window to explore the physical mechanism responsible for the collective phenomenon.

Extreme boundary conditions and random tilings

Standard statistical mechanical or condensed matter arguments tell us that bulk properties of a physical system do not depend too much on boundary conditions. Random tilings of large regions provide counterexamples to such intuition, as illustrated by the famous 'arctic circle theorem' for dimer coverings in two dimensions. In these notes, I discuss such examples in the context of critical phenomena, and their relation to 1+1d quantum particle models. All those turn out to share a common feature: they are inhomogeneous, in the sense that local densities now depend on position in the bulk. I explain how such problems may be understood using variational (or hydrodynamic) arguments, how to treat long range correlations, and how non trivial edge behavior can occur. While all this is done on the example of the dimer model, the results presented here have much greater generality. In that sense the dimer model serves as an opportunity to discuss broader methods and results. [These notes require only a basic knowledge of statistical mechanics.]