Correlation Of Fluctuations Research Articles

Deficits of Visual Cortex Function in Acute Acquired Concomitant Esotropia Patients.

The purpose of this study was to explore the cortical deficits of patients with acquired concomitant esotropia (AACE) using the resting-state functional magnetic resonance imaging (rs-fMRI) technique. Rs-fMRI signals from 25 patients with AACE and 25 matched controls were collected. The repeated-measures analysis of variance (RM-ANOVA) test and two-sample t-test were used to investigate statistical differences of the amplitudes of low-frequency fluctuation (ALFF) signals and correlation analysis was performed to validate the relationship of signal change and clinical features. The AACE group showed decreased ALFF in both hemispheres symmetrically (t = 0.38, P = 0.71), with peak t in both middle occipital gyrus. The ALFF signal from the upper left inferior frontal gyrus was negatively correlated with the age of onset (r = 0.62, P = 0.0008), and the ALFF signal from the right superior temporal gyrus was negatively correlated with the near work hours (r = 0.63, P = 0.0008). The ALFF signal in the left fusiform gyrus was positively correlated with both near (r = 0.48, P = 0.01) and far (r = 0.44, P = 0.03) deviation, whereas it was only positively correlated with far deviation (r = 0.44, P = 0.03) in the right. Besides, the age of onset and the near work hour were independent factors of signal changes. Using the ALFF signal of rs-fMRI, we found functional deficits in the primary visual cortex and dorsal pathway in patients with AACE. There were functional changes in the fusiform gyrus, and the greater the deviation angle, the higher the changing level. These findings reveal the association of AACE and the visual center, giving us more clues about the treatment of AACE.

Anisotropic dynamics of an interfacial enzyme active site observed using tethered substrate analogs and ultrafast 2D IR spectroscopy.

Enzymes accelerate the rates of biomolecular reactions by many orders of magnitude compared to bulk solution, and it is widely understood that this catalytic effect arises from a combination of polar pre-organization and electrostatic transition state stabilization. A number of recent reports have also implicated ultrafast (femtosecond-picosecond) timescale motions in enzymatic activity. However, complications arising from spatially-distributed disorder, the occurrence of multiple substrate binding modes, and the influence of hydration dynamics on solvent-exposed active sites still confound many experimental studies. Here we use ultrafast two-dimensional infrared (2D IR) spectroscopy and covalently-tethered substrate analogs to examine dynamical properties of the promiscuous Pyrococcus horikoshii ene-reductase (PhENR) active site in two binding configurations mimicking proposed "inactive" and "reactive" Michaelis complexes. Spectral diffusion measurements of aryl-nitrile substrate analogs reveal an end-to-end tradeoff between fast (sub-ps) and slow (>5ps) motions. Fermi resonant aryl-azide analogs that sense interactions of coupled oscillators are described. Lineshape and quantum beat analyses of these probes reveal characteristics that correlate with aryl-nitrile frequency fluctuation correlation functions parameters, demonstrating that this anisotropy is an intrinsic property of the water-exposed active site, where countervailing gradients of fast dynamics and disorder in the reactant ground state are maintained near the hydration interface. Our results suggest several plausible factors leading to state-selective rate enhancement and promiscuity in PhENR. This study also highlights a strategy to detect perturbations to vibrational modes outside the transparent window of the mid-IR spectrum, which may be extended to other macromolecular systems.

Trade-offs between cost and information in cellular prediction

Living cells can leverage correlations in environmental fluctuations to predict the future environment and mount a response ahead of time. To this end, cells need to encode the past signal into the output of the intracellular network from which the future input is predicted. Yet, storing information is costly while not all features of the past signal are equally informative on the future input signal. Here, we show for two classes of input signals that cellular networks can reach the fundamental bound on the predictive information as set by the information extracted from the past signal: Push-pull networks can reach this information bound for Markovian signals, while networks that take a temporal derivative can reach the bound for predicting the future derivative of non-Markovian signals. However, the bits of past information that are most informative about the future signal are also prohibitively costly. As a result, the optimal system that maximizes the predictive information for a given resource cost is, in general, not at the information bound. Applying our theory to the chemotaxis network of Escherichia coli reveals that its adaptive kernel is optimal for predicting future concentration changes over a broad range of background concentrations, and that the system has been tailored to predicting these changes in shallow gradients.

Clinical Correlation of Retinal Fluid Fluctuation Represented by Fluctuation Index in Wet Age-Related Macular Degeneration: TOWER Study Report 2.

To explore outcomes and biomarkers associated with retinal fluid instability represented by a new parameter in neovascular age-related macular degeneration (nAMD). Patients with treatment-naïve nAMD receiving anti-vascular endothelial growth factor (VEGF) injections for a duration of 1 to 3 years were consecutively reviewed. Fluctuation Index (FI) of each eye, calculated by averaging the sum of differences in 1-mm central subfield thickness between each follow-up from months 3 to 24, was arranged into ascending order from the lowest to the highest and split equally into low, moderate, and high fluctuation groups. Outcomes were analyzed at 24 months. Of 558 eyes, FI values showed a negative correlation with a degree-response gradient with 24-month visual improvement. After controlling for baseline best-corrected visual acuity and potential confounders, eyes with low fluctuation gained more Early Treatment Diabetic Retinopathy Study letters than those in the moderate and high fluctuation group (Δ, 10.1 and 14.0 letters, respectively). Significant best-corrected visual acuity improvement from baseline to month 24 (11.8 letters) was observed exclusively in the low fluctuation group despite the indifference in the number of injections and types of anti-VEGF drug used among groups. Patients presenting with central subfield thickness of ≥405 µm or intraretinal fluid coinciding with subretinal fluid showed a significant association with foveal thickness instability during the maintenance phase. Apart from the central subfield thickness values, unstable macular thickening represented by the FI was associated with some baseline features and may contribute to substandard visual outcomes. FI may be a valuable tool for assessing therapeutic adequacy in the treatment of nAMD.

Optical sparse telescope arrays and scintillation noise

ABSTRACT Fresnel propagation of starlight after it passes through high altitude turbulence in the Earth’s atmosphere results in random fluctuations of the intensity at ground level, known as scintillation. This effect adds random noise to photometric measurements with ground-based optical telescopes. Spatial correlation of the intensity fluctuations means that the fractional photometric noise due to scintillation may be substantially smaller for a sparse array of small aperture telescopes than for a single large aperture of the same total area. Assuming that the photometric noise for each telescope is independent, averaging the light curves measured by N telescopes reduces the noise by a factor of $\sqrt{N}$. For example, for bright stars, the signal-to-noise ratio of a 2.54 m telescope can be achieved for an array of thirty 20 cm telescopes if the scintillation noise measured for each telescope is uncorrelated. In this paper, we present results from simulation and from observations at the Isaac Newton Telescope. These explore the impact that several parameters have on the measured correlation of the scintillation noise between neighbouring telescopes. We show that there is significant correlation between neighbouring telescopes with separations parallel to the wind direction of the dominant high altitude turbulent layer. We find that the telescopes in an array should be separated by at least twice their aperture diameter so that there is negligible correlation of the photometric noise. We discuss additional benefits of using sparse telescope arrays, including reduced cost and increased field of view.

Multigenerational memory in bacterial size control.

Cells maintain a stable size as they grow and divide. Inspired by the available experimental data, most proposed models for size homeostasis assume size-control mechanisms that act on a timescale of one generation. Such mechanisms lead to short-lived autocorrelations in size fluctuations that decay within less than two generations. However, recent evidence from comparing sister lineages suggests that correlations in size fluctuations can persist for many generations. Here we develop a minimal model that explains these seemingly contradictory results. Our model proposes that different environments result in different control parameters, leading to distinct inheritance patterns. Multigenerational memory is revealed in constant environments but obscured when averaging over many different environments. Inferring the parameters of our model from Escherichia coli size data in microfluidic experiments, we recapitulate the observed statistics. Our paper elucidates the impact of the environment on cell homeostasis and growth and division dynamics.

Study of neutron density fluctuation and neutron-proton correlation in Au+Au collisions using PYTHIA8/Angantyr* *Supported in part by the Natural Science Foundation of Henan Province, China (212300410386), the Key Research Projects of Henan Higher Education Institutions (20A140024), the Scientific Research Foundation of Hubei University of Education for Talent Introduction (ESRC20220028, ESRC20230002), the NSFC (12005114) and NSFC key Grant (12061141008), and the

Utilizing the PYTHIA8 Angantyr model, which incorporates the multiple-parton interaction (MPI) based color reconnection (CR) mechanism, we study the relative neutron density fluctuation and neutron-proton correlation in Au+Au collisions at = 7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV. In this study, we not only delve into the dependence of these two remarkable observations on rapidity, centrality, and energy, but also analyze their interplay with the MPI and CR. Our results show that the light nuclei yield ratio of protons, deuterons, and tritons, expressed by the elegant expression , remains unchanged even as the rapidity coverage and collision centrality increase. Interestingly, we also reveal that the effect of CR is entirely dependent on the presence of the MPI; CR has no impact on the yield ratio if the MPI is off. Our findings further demonstrate that the light nuclei yield ratio experiences a slight increase with increasing collision energy, as predicted by the PYTHIA8 Angantyr model; however, it cannot describe the non-monotonic trend observed by the STAR experiment. Based on the Angantyr model simulation results, it is essential not to overlook the correlation between neutron and proton fluctuations. The Angantyr model is a good baseline for studying collisions in the absence of a quark-gluon plasma system, given its lack of flow and jet quenching.

Environmental fluctuations explain the universal decay of species-abundance correlations with phylogenetic distance

Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches-which combine phylogenetic relationships between species with community ecology-have the potential to disentangle such forces but are often hard to connect with quantitative predictions from theoretical models. On the other hand, macroecology, which focuses on statistical patterns of abundance and diversity, provides natural connections with theoretical models but often neglects interspecific correlations and interactions. Here, we propose a unified framework combining both such approaches to analyze microbial communities. In particular, by using both cross-sectional and longitudinal metagenomic data for species abundances, we reveal the existence of an empirical macroecological law establishing that correlations in species-abundance fluctuations across communities decay from positive to null values as a function of phylogenetic dissimilarity in a consistent manner across ecologically distinct microbiomes. We formulate three variants of a mechanistic model-each relying on alternative ecological forces-that lead to radically different predictions. From these analyses, we conclude that the empirically observed macroecological pattern can be quantitatively explained as a result of shared population-independent fluctuating resources, i.e., environmental filtering and not as a consequence of, e.g., species competition. Finally, we show that the macroecological law is also valid for temporal data of a single community and that the properties of delayed temporal correlations can be reproduced as well by the model with environmental filtering.

Abnormal voxel-mirrored homotopic connectivity in first-episode, drug-naïve patients with obsessive-compulsive disorder.

Prior studies suggest that obsessive-compulsive disorder (OCD) can cause both anatomical and functional variations in the brain, but to date, altered functional synchronization between two functional hemispheres remains unclear in OCD patients. Voxel-mirrored homotopic connectivity (VMHC) is defined as the temporal correlation of spontaneous low-frequency blood oxygenation level-dependent signal fluctuations across mirror regions of hemisphere revealing the homotopic connectivity between each voxel in one hemisphere and its mirrored counterpart in the contralateral hemisphere. To investigate the alterations of brain regional function and VMHC in patients with OCD, the current study enrolled 103 OCD patients and 118 healthy controls, undergoing resting-state functional magnetic resonance imaging. Compared to healthy controls (HCs), patients had decreased VMHC in bilateral cerebellum, lingual and fusiform gyrus; bilateral paracentral lobule, pre and postcentral gyrus; and bilateral superior and middle temporal gyrus, putamen and bilateral precuneus without global signal regression. And we found mostly similar results after regressing global signals; apart from the regions mentioned above, decreased in bilateral cuneus and calcarine was also showed. Furthermore, the mean VMHC values of the left cerebellum were negatively correlated with the obsession scores (ρ = -.204, π = .039). The decreased values in right fusiform and putamen were negatively correlated with duration of disease (ρ = -.205, π = .038; ρ = -.196, π = .047). We confirmed a significant VMHC reduction in OCD patients in broad areas. Our findings suggest that the patients tend to disconnect information exchange across hemispheres.

Correlations of spin splitting and orbital fluctuations due to 1/f charge noise in the Si/SiGe quantum dot

Fluctuations in electric fields can change the position of a gate-defined quantum dot (QD) in a semiconductor heterostructure. In the presence of magnetic field gradient, these stochastic shifts of electron's wavefunction lead to fluctuations of electron's spin splitting. The resulting spin dephasing due to charge noise limits the coherence times of spin qubits in isotopically purified Si/SiGe quantum dots. We investigate the spin splitting noise caused by such a process due to microscopic motion of charges at the semiconductor-oxide interface. We compare effects of isotropic and planar displacement of the charges and estimate their densities and typical displacement magnitudes that can reproduce experimentally observed spin splitting noise spectra. We predict that for a defect density of 1010 cm−2, visible correlations between noises in spin splitting and in energy of electron's ground state in the quantum dot are expected.

Response to multiplicative noise: The cross-spectrum of membrane voltage fluctuation and voltage-independent conductance noise

We reveal that the correlation of voltage fluctuation and voltage-independent conductance noise, rather than the magnitude of the latter, explains most of the former. Being the response function in the spectral domain, the cross-spectrum has an order-three scaling law originating in the imaginary part, and it can be divided into three phases: left the real part dominant phase; right the imaginary part dominant phase; and center the transition phase. Since the coherence in the left phase has a greater decay rate than that in the right phase, an additional peak appears in the transition phase. All of these results imply that the effects of conductance noise, being multiplicative, cannot be characterized by the concept of impedance—which is adopted from the field of equilibrium thermodynamics.

Hanbury Brown-Twiss approach for imaging through a dynamic scattering medium.

The Hanbury Brown-Twiss approach, associated with the correlation of intensity fluctuations at two different points in a wave field, unveils fundamental aspects of light. Here, we propose and experimentally demonstrate an imaging and phase recovery technique through a dynamic scattering medium using the Hanbury Brown-Twiss approach. A detailed theoretical basis is presented and verified by experimental demonstrations. To validate the application of the proposed technique, the randomness of the dynamically scattered light is exploited using temporal ergodicity for evaluating the correlation of intensity fluctuations and consequently applying it in the reconstruction of the object hidden behind the dynamic diffuser.

Replica symmetry breaking in random lasers: A Monte Carlo study with mean-field interacting photonic random walkers

We investigate the replica symmetry breaking (RSB) phenomenon in random lasers (RLs) through Monte Carlo simulations employing photonic random walkers that diffuse and get randomly scattered in the active medium. The walkers interact not only with the population of excited atoms, but also among themselves, in a mean-field-type approach based on the Langevin equation for the stochastic dynamics of RL modes. We obtain the proper profile of the distribution $P(q)$ of the Parisi overlap parameter in the RSB glassy phase, with two pronounced side maxima at $q=\ifmmode\pm\else\textpm\fi{}1$ above the RL threshold, in contrast with some recent numerical studies. Remarkably, when the interactions among photonic walkers are not included, a replica-symmetric profile with a single maximum of $P(q)$ at $q=0$ is found for any excitation energy. We further study the Gaussian and L\'evy emission regimes and statistical correlations of intensity fluctuations in distinct modes of the same spectrum, using a Pearson correlation coefficient recently applied to RLs. Our findings are consistent with experimental results for the intensity statistics and $P(q)$ distributions in RL materials.

Anomalous finite-size effect on the magnetostructural transition in CrN

We report a systematic investigation of the finite-size effect on magnetostructural transition in CrN based on a series of nanoparticle samples with various sizes prepared by a high-pressure method, leading to the discovery of anomalous critical behaviors near transition, especially for spin correlation length. Such critical anomalies are presumably attributed to the strong spin-lattice coupling in this nitride, because the spin correlation of fluctuation can be greatly affected by the concurrent structural distortion. Using the conventional Gibbs-Thomson theorem and size-dependent effect, the scaling relationship between transition temperature and spin correlation length is deduced by involving a term of the transition-induced volume change that rationalizes the role that the lattice degree of freedom played during magnetic ordering. A phenomenological model is also established for understanding the kinetics and dynamics of magnetic fluctuation at transition in a finite-size system. In addition, our results also show that CrN nanoparticles possess a compressed surface shell, which can be described by Laplace pressure, obeying a unique $\frac{1}{{d}^{1.8}}$ finite-size scaling law.

Analysis and prediction of the changes in groundwater resources under heavy precipitation and ecological water replenishment

Abstract Identifying the influence of heavy precipitation and ecological water replenishment (EWR) on groundwater resources is essential for groundwater resources management and risk prevention. This study innovatively developed a groundwater resource analysis and prediction model integrated with the water level fluctuation method, correlation analysis, and machine learning method under the influence of heavy precipitation and EWR. Water level fluctuation method results showed that compared with January 1, 2021, the groundwater resources of the study area increased 4.46 × 108 m3 on August 28. Compared with small flow of EWR, heavy precipitation was the main contributor to the rise in the groundwater level. Correlation analysis found that elevation, specific yield, and permeability coefficient show positive correlations with groundwater resource recharge. Machine learning results showed that among the water level prediction models of 35 monitoring wells, extreme gradient boosting (XGB) and random forest (RF) performed best in 30 wells and five wells, respectively. The increase in groundwater storage predicted deviated from the actual value by only 0.6 × 107 m3 (prediction bias of 1.3%), indicating that the model prediction performance was good under the heavy precipitation condition. This study can help to better understand the change trend of groundwater resources under the conditions of heavy precipitation and EWR.

Spin Chaos Dynamics in Classical Random Dipolar Interactions

The stochastic nature of magnetization dynamics of dipole–dipole interactions described by the Landau–Lifshitz–Gilbert equation without considering the Gilbert damping parameter is investigated. It is shown that the occurrence of the complex dynamic states depends on the spatial anisotropy of interactions on one hand and the lattice geometry on the other. It is observed from the higher-order moments of the magnetization fluctuations that two significant dynamical regimes, regular and chaos, may be obtained depending on the perturbation strength. Relying on the Hurst exponent obtained by the standard deviation principle, the correlation and persistence of the magnetization fluctuations are analyzed. The results also exhibit a transition from an anti-correlated to a positively correlated system as the relevant parameters of the system vary.

Breakdown of long-range spatial correlations of infraslow amplitude fluctuations of EEG oscillations in patients with current and past major depressive disorder.

Identifying biomarkers for depression from brain activity is important for the diagnosis and treatment of depression disorders. We investigated spatial correlations of the amplitude fluctuations of electroencephalography (EEG) oscillations as a potential biomarker of depression. The amplitude fluctuations of EEG oscillations intrinsically reveal both temporal and spatial correlations, indicating rapid and functional organization of the brain networks. Amid these correlations, long-range temporal correlations are reportedly impaired in patients with depression, exhibiting amplitude fluctuations closer to a random process. Based on this occurrence, we hypothesized that the spatial correlations of amplitude fluctuations would also be altered by depression. In the present study, we extracted the amplitude fluctuations of EEG oscillations by filtering them through infraslow frequency band (0.05-0.1 Hz). We found that the amplitude fluctuations of theta oscillations during eye-closed rest depicted lower levels of spatial correlation in patients with major depressive disorder (MDD) compared to control individuals. This breakdown of spatial correlations was most prominent in the left fronto - temporal network, specifically in patients with current MDD rather than in those with past MDD. We also found that the amplitude fluctuations of alpha oscillations during eye-open rest exhibited lower levels of spatial correlation in patients with past MDD compared to control individuals or patients with current MDD. Our results suggest that breakdown of long-range spatial correlations may offer a biomarker for the diagnosis of depression (current MDD), as well as the tracking of the recovery from depression (past MDD).

Fluctuation-driven excess noise near superconducting phase transition

We discuss intrinsic mechanisms of nonequilibrium excess noise in superconducting devices and transition edge sensors. In particular, we present an overview of fluctuation-driven contributions to the current noise in the vicinity of the superconducting transition. We argue that sufficiently close to the critical temperature fluctuations of conductivity may become correlated provided that the rate of quasiparticle relaxation is slow as compared to dynamics of superconducting fluctuations. In this regime, fluctuations of conductivity adiabatically follow the fluctuations of the electron distribution. This leads to a substantial enhancement of current noise. The corresponding spectral power density of noise has a Lorentzian shape in the frequency domain while its magnitude scales proportionally to the inelastic relaxation time. It also sensitively depends on the dephasing and Ginzburg–Landau timescales. Further estimates suggest that this mechanism dominates over the conventional temperature fluctuations in the same range of parameters. To describe these effects microscopically, we use the nonequilibrium Keldysh technique in the semiclassical approximation of superconductivity with Boltzmann–Langevin random forces to account for correlations of fluctuations.

The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market

The impact of the investor sentiment on China’s capital market price volatility is concerned under the perspective of the behavioral finance. Firstly, in terms of the existing methods of establishing the investor sentiment index, the composite investor sentiment index which include six indicators (five objective indicators and a subjective indicator) are obtained. Secondly, VMD-LSTM (Variational Mode Decomposition and Long Short Term Memory) hybrid neural network model is used to decompose and restructure the investor sentiment index and the Shanghai Security Exchange Composite Index (SSEC) into the short-term, medium-term and long-term trend. Each trend is trained to obtain the forecasting results in three different time scales, and then to achieve the final predicting results by superimposing the output of each trend. Furthermore, compare with other prediction methods, the model can indeed improve the overall predicting accuracy. Finally, GARCH model and the co-integration error regression model are used to discuss the fluctuation correlation and VAR (Vector Auto-regression) models are established to analyze the causality between the stock market indices and the investor sentiment index.

Establishment of correlation for the pressure fluctuations on the low-head Francis turbine in the draft tube cone from the model test

Pressure fluctuation is an essential metric for assessing the effectiveness of the functioning of a hydraulic turbine. During the operation of the hydraulic turbine, pressure fluctuations occur under varied load conditions. An advanced data acquisition system and measurement setup were designed to investigate the pressure fluctuation characteristics in the Francis turbine model with three pressure heads. The operating points for pressure fluctuations investigations ranged from lower part load to overload condition. The plant sigma condition is studied extensively under three different heads, i.e. 30.45 m, 31.98 m and 38.78 m. The miniature-type pressure transducers are used for the investigations. Three pressure sensors, one in the inlet of the spiral case, second and third in the draft tube upstream and downstream respectively, are installed. The measurements were conducted in different operating conditions considering the prototype output power of 16.7 MW, 20.3 MW, 27.8 MW, 34.3 MW and 40.4 MW. A correlation has been developed to represent the variation of draft tube cone pressure fluctuations concerning head and output power.