Strong Cross-correlation Research Articles

Spatiotemporal Variability of Groundwater Quality for Irrigation: A Case Study in Mimoso Alluvial Valley, Semiarid Region of Brazil

Alluvial aquifers are vital for agricultural communities in semiarid regions, where groundwater quality is often constrained by seasonal and spatial salinity variations. This study employed geostatistical methods to analyze the spatial and temporal variability of electrical conductivity (EC) and the sodium adsorption ratio (SAR) and elaborate an indicative quality map in the Mimoso Alluvial Aquifer, Pernambuco, Brazil. Groundwater samples were collected and analyzed for cations, total hardness (TH), and the percentage of sodium (PS). Moreover, the relation between EC and the SAR was used to determine the groundwater quality for irrigation. Cation concentrations followed the order Ca2+ > Mg2+ > Na+ > K+. EC and the SAR exhibited medium to high variability, with spatial dependence ranging from moderate to strong, and presented a strong cross-spatial dependence. Results showed that sequential Gaussian simulation (SGS) provided a more reliable groundwater classification for agricultural purposes compared to kriging methods, enabling a more rigorous evaluation. Based on the strong geostatistical cross correlation between EC and RAS, a novel water quality index was proposed, properly identifying regions with lower groundwater quality. The resulting spatial indicator maps classified groundwater as suitable (64.7%), restricted use (2.08%) and unsuitable (2.38%) for irrigation. The groundwater quality maps indicated that groundwater was mostly suitable for agriculture, except in silty areas, also corresponding to regions with low hydraulic conductivity at the saturated zone. Soil texture, rainfall, and water extraction significantly influenced spatial and temporal patterns of groundwater quality. Such correlations allow a better understanding of the groundwater quality in alluvial valleys, being highly relevant for water resources management in semiarid areas.

Modeling correlated-noise in silicon spin qubit device

Silicon-based spin qubit platform is a promising candidate for the hardware realization of quantum computing. Charge noise, however, plays a critical role in limiting the fidelity and scalability of silicon-based quantum computing technologies. This work presents Green’s transfer function approach to simulate the correlated noise power spectral density (PSD) in silicon spin qubit devices. The simulation approach relates the dynamics of the charge noise source of two-level fluctuators (TLFs) to the correlated noise of spin qubit device characteristics through a transfer function. It allows the noise auto-correlation and cross correlation between any pairs of physical quantities of interest to be systematically computed and analyzed. Because each spin qubit device involves only a small number of TLFs due to its nanoscale device size, the distribution of TLFs impacts the noise correlation significantly. In both a two-qubit quantum gate and a spin qubit array device, the charge noise shows strong cross correlation between neighboring qubits. The simulation results also reveal a phase-flipping feature of the noise cross-PSD between neighboring spin qubits, consistent with a recent experiment.

Historical invasion rates vary among insect trophic groups

Globalization has spread thousands of invasive insect species into new world regions,1,2,3 causing severe losses in ecosystem services. Previous work proposed that plant invasions facilitate insect invasions through the creation of niches for non-native herbivores.3,4,5,6 Despite the impact of insect invasions, a comprehensive understanding is lacking on how invasion success varies among insect feeding groups. We therefore compiled the predominant larval trophic groups (herbivores, predators, parasites, detritivores, and brood-carers) for 5,839 non-native insect species in nine world regions to compare (1) proportions of species in each group between non-native species and the world's fauna, (2) how invasion success for each trophic group has changed over the last three centuries, and (3) how historical herbivore invasions are related to plant invasions over time and parasite invasions are related to herbivores. We find that herbivores represent a significantly larger proportion (52.4%) among non-native insects compared with the world fauna (38.4%), whereas proportions of non-native detritivores (including fungivores), predators, and brood-carers are significantly lower; parasite proportions do not significantly differ. Predators and detritivores dominated among invasions in the 18th century but subsequently diminished, likely due to changing invasion pathways, whereas proportions of herbivores, parasites, and brood-carers increased over time. We found herbivore invasions to lag 80 years behind plant invasions, whereas parasitoids appear to co-invade with their herbivore hosts. The dominance of herbivores among non-native insects and their strong cross-correlation with plant invasions further strengthens the hypothesis that plant invasions drive the global rise in numbers of non-native insects.

Economic Echoes of Conflict: Evaluating the Palestine-Israel War’s Influence on Middle Eastern Markets

ABSTRACT This study examines the Palestine-Israel conflict’s effects on Middle Eastern financial markets, including conventional and Islamic indices. Employing wavelet cross-correlation, global VAR (GVAR), and Granger causality analyses, we identify complex patterns in pre-conflict geopolitical risk (GPR) and stock returns, including diverse lead/lag behaviors and amplitude fluctuations. Post-conflict, these dynamics show smoother adjustments and stronger cross-correlations. The pre-conflict wavelet GVAR analysis reveals country-specific reactions to anticipated GPR shocks, marked by asymmetric responses starting around 20 days post-shock and varying across nations. This period also features significant shock spillovers in stock returns, both positive and negative. During the conflict, initial reactions include substantial spikes in raw stock returns, suggesting possible co-crash scenarios. These evolve into predominantly positive short-term shock spillovers, with medium and long-term responses suggesting stock markets as potential safe havens. Lastly, wavelet Granger causality analysis reveals bidirectional causality between GPR and stock returns over the long term, with specific countries showing varied causality patterns during the conflict. The inclusion of Islamic indices demonstrates homogeneous responses to GPR shocks, similar to conventional markets, highlighting the integrated nature of these markets. This study underscores the complex temporal dynamics of market responses to geopolitical shocks and provides insights for policymakers and investors.

Green cryptocurrencies versus sustainable investments dynamics: Exploration of multifractal multiscale analysis, multifractal detrended cross-correlations and nonlinear Granger causality

Green cryptocurrencies versus sustainable investments dynamics: Exploration of multifractal multiscale analysis, multifractal detrended cross-correlations and nonlinear Granger causality

Assessing the time variability of GIEMS-2 satellite-derived surface water extent over 30 years

Inland waters, especially wetlands, play a crucial role in biodiversity, water resources and climate, and contribute significantly to global methane emissions. This study investigates the seasonal and inter-annual variability of the 0.25° × 0.25° surface water extent (SWE) from the Global Inundation Extent from Multi-Satellites (GIEMS-2) extended to a 30-year time series (1992–2020). Comparison with MODIS-derived SWE, CYGNSS-derived SWE and the Global Lakes and Wetlands Database (GLWD) shows consistent spatial patterns globally and over 10 different basins, although there are discrepancies in extent, partly due to different resolutions of the initial satellite observations. Strong cross-correlation (>0.8) in seasonal variability is observed when comparing GIEMS-2 with MODIS, CYGNSS and river discharge in most of the basins studied. Encouraging similarities were found in the inter-annual variability in most basins (cross-correlation >0.6) between GIEMS-2 and MODIS over 20 years, and between GIEMS-2 and river discharge over long time series, including over the Amazon and the Congo basins. These results highlight the reliability of GIEMS-2 in detecting changes in SWE in different environments, especially under dense vegetation, making it a valuable resource for calibrating hydrological models and studying global methane emissions.

Promotional Language (Hype) in Abstracts of Publications of National Institutes of Health–Funded Research, 1985-2020

Investigators applying for National Institutes of Health (NIH) funding increasingly use promotional language (or hype) that has the potential to undermine objective evaluation. Whether or not the same investigators use hype in subsequent research reports has yet to be investigated. To assess changes in the use of hype in journal abstracts reporting research funded by the NIH and to compare those trends with previously reported trends in the associated NIH funding applications. This cross-sectional study assessed trends (from 1985 to 2020) in the use of promotional adjectives in abstracts of journal articles reporting NIH-funded research, and then compared those trends with previously reported trends for the associated NIH funding applications. Articles included in analyses had abstracts available in PubMed. Absolute change for the 139 adjective forms that have previously been identified as representing hype in NIH funding applications was measured as the difference in frequency between 1985 and 2020. Relative change was measured as the percentage change in frequency in 2020 relative to 1985, or the first year of occurrence. Consistency of change was measured by the rank order correlation (Kendall τ). Concordance between longitudinal trends in the journal abstracts and NIH funding applications was measured by the rank-order cross-correlation. In a total of 2 394 480 journal abstracts, all 139 adjective forms were identified in 2 793 592 total occurrences. Among these adjectives, 133 increased in absolute frequency by 5335 words per million (wpm), with a mean (SD) relative increase of 1404% (2371%). The largest absolute increases were for novel (524 wpm), important (414 wpm), and key (378 wpm). The largest relative increases were for scalable (22 wpm [19 964%]), unmet (23 wpm [12 126%]), and tailored (40 wpm [8169%]). The mean (SD) correlation for all adjectives was 0.70 (0.30) with 95 adjectives showing a strong positive correlation (τ > 0.7; P < .001), 24 a moderate positive correlation (0.5 < τ < 0.7; P < .001), and 3 a moderate negative correlation (-0.5 < τ < -0.7; P < .001). The mean (SD) cross-correlation was 0.64 (0.19) with 61 of the 139 adjectives showing a strong positive cross-correlations (τ > 0.7; P < .001), 53 a moderate positive cross-correlations (0.5 < τ < 0.7; P < .001), and 3 a moderate negative cross-correlation (-0.7 < τ < -0.5; P < .001). In this analysis of journal abstracts reporting NIH-funded research from 1985 to 2020, levels of promotional language were found to be increasing and trends were closely associated with previously reported trends in the related NIH funding applications. This suggests that increasing levels of salesmanship may in part be a downstream effect of salesmanship infused during earlier stages of the research cascade.

Buckyball-metal Complexes as Potential Carriers of Astronomical Unidentified Infrared Emission Bands

Efforts over 40 yr still leave the source of astronomical infrared emission bands largely unidentified. Here, we report the first laboratory infrared (6–25 μm) spectra of gas-phase fullerene-metal complexes, [C60-Metal]+ (Metal = Fe, V) and show with density functional theory calculations that complexes of C60 with cosmically abundant metals, including Li, Na, K, Mg, Ca, Al, V, and Fe, all have similar spectral patterns. Comparison with observational infrared spectra from several fullerene-rich planetary nebulae demonstrates a strong positive linear cross-correlation. The infrared features of [C60-Metal]+ coincide with four bands attributed earlier to neutral C60 bands and in addition also with several bands unexplained to date. Abundance and collision theory estimates indicate that [C60-Metal]+ could plausibly form and survive in astrophysical environments. Hence, [C60-Metal]+ are proposed as promising carriers, in supplement to C60, of observational bands, potentially representing the largest molecular species in space other than C60, C60 +, and C70.

Synthesis, characterization of 4,4′-((1E,1′E)-hydrazine-1,2-diylidenebis(methanylylidene)) diphenol and the inclusion complex with γ-cyclodextrin as a fluorescent probe for detection of Al3+

Synthesis, characterization of 4,4′-((1E,1′E)-hydrazine-1,2-diylidenebis(methanylylidene)) diphenol and the inclusion complex with γ-cyclodextrin as a fluorescent probe for detection of Al3+

Non-Brownian diffusion and chaotic rheology of autophoretic disks.

The dynamics of a two-dimensional autophoretic disk is quantified as a minimal model for the chaotic trajectories undertaken by active droplets. Via direct numerical simulations, we show that the mean-square displacement of the disk in a quiescent fluid is linear at long times. Surprisingly, however, this apparently diffusive behavior is non-Brownian, owing to strong cross correlations in the displacement tensor. The effect of a shear flow field on the chaotic motion of an autophoretic disk is examined. Here, the stresslet on the disk is chaotic for weak shear flows; a dilute suspension of such disks would exhibit a chaotic shear rheology. This chaotic rheology is quenched first into a periodic state and ultimately a steady state as the flow strength is increased.

NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis

NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis

A computational musculoskeletal arm model for assessing muscle dysfunction in chronic obstructive pulmonary disease.

Computational models have been used extensively to assess diseases and disabilities effects on musculoskeletal system dysfunction. In the current study, we developed a two degree-of-freedom subject-specific second-order task-specific arm model for characterizing upper-extremity function (UEF) to assess muscle dysfunction due to chronic obstructive pulmonary disease (COPD). Older adults (65years or older) with and without COPD and healthy young control participants (18 to 30years) were recruited. First, we evaluated the musculoskeletal arm model using electromyography (EMG) data. Second, we compared the computational musculoskeletal arm model parameters along with EMG-based time lag and kinematics parameters (such as elbow angular velocity) between participants. The developed model showed strong cross-correlation with EMG data for biceps (0.905, 0.915) and moderate cross-correlation for triceps (0.717, 0.672) within both fast and normal pace tasks among older adults with COPD. We also showed that parameters obtained from the musculoskeletal model were significantly different between COPD and healthy participants. On average, higher effect sizes were achieved for parameters obtained from the musculoskeletal model, especially for co-contraction measures (effect size = 1.650 ± 0.606, p < 0.001), which was the only parameter that showed significant differences between all pairwise comparisons across the three groups. These findings suggest that studying the muscle performance and co-contraction, may provide better information regarding neuromuscular deficiencies compared to kinematics data. The presented model has potential for assessing functional capacity and studying longitudinal outcomes in COPD.

Prewhitening and normalization help detect a strong cross-correlation between daily wastewater SARS-CoV-2 RNA abundance and COVID-19 cases in a community

Significant cross-correlation was observed between daily wastewater SARS-CoV-2 RNA abundance and clinical case numbers (with a two-day lag) after prewhitening and normalization of the time series data.

Dynamical Masses of the Primary Be Star and Secondary sdB Star in the Single-lined Binary κ Dra (B6 IIIe)

Because many classical Be stars may owe their nature to mass and angular-momentum transfer in a close binary, the present masses, temperatures, and radii of their components are of high interest for comparison to stellar evolution models. Object κ Dra is a 61.5 day single-lined binary with a B6 IIIe primary. With the CHARA Array instruments MIRC/MIRC-X and MYSTIC, we detected the secondary at (approximately photospheric) flux ratios of 1.49% ± 0.10% and 1.63% ± 0.09% in the H and K band, respectively. From a large and diverse optical spectroscopic database, only the radial velocity curve of the Be star could be extracted. However, employing the parallaxes from Hipparcos and Gaia, which agree within their nominal 1σ errors, we could derive the total mass and found component masses of 3.65 ± 0.48 and 0.426 ± 0.043 M ⊙ for the Be star and the companion, respectively. Previous cross-correlation of the observed FUV spectrum with O-type subdwarf (sdO) spectral model templates had not detected a companion belonging to the hot sdO population known from ∼20 earlier-type Be stars. Guided by our full 3D orbital solution, we found a strong cross-correlation signal for a stripped subdwarf B-type companion (FUV flux ratio of 2.3% ± 0.5%), enabling the first firm characterization of such a star and making κ Dra the first mid- to late-type Be star with a directly observed subdwarf companion.

Non-classical correlations over 1250 modes between telecom photons and 979-nm photons stored in 171Yb3+:Y2SiO5

Quantum repeaters based on heralded entanglement require quantum nodes that are able to generate multimode quantum correlations between memories and telecommunication photons. The communication rate scales linearly with the number of modes, yet highly multimode quantum storage remains challenging. In this work, we demonstrate an atomic frequency comb quantum memory with a time-domain mode capacity of 1250 modes and a bandwidth of 100 MHz. The memory is based on a Y2SiO5 crystal doped with 171Yb3+ ions, with a memory wavelength of 979 nm. The memory is interfaced with a source of non-degenerate photon pairs at 979 and 1550 nm, bandwidth-matched to the quantum memory. We obtain strong non-classical second-order cross correlations over all modes, for storage times of up to 25 μs. The telecommunication photons propagated through 5 km of fiber before the release of the memory photons, a key capability for quantum repeaters based on heralded entanglement and feed-forward operations. Building on this experiment should allow distribution of entanglement between remote quantum nodes, with enhanced rates owing to the high multimode capacity.

Conservation in the Amazon rainforest and Google searches: A DCCA approach.

In this paper we analyze the descriptive statistics of the Google search volume for the terms related to the National Reserve of Copper and Associates (RENCA), a Brazilian mineral reserve in the Amazon of 4.6 million hectares, before and after the government signed the decree releasing it for exploration. First, we analyze the volume of searches for expressions related to RENCA in Google Trends using descriptive statistics; second, we assess the cross-correlation coefficient ρDCCA, which measures the cross-correlation between two nonstationary time series across different time scales. After the government announced the release of the RENCA reserve, there was an increase in the average volume of Google searches for related terms, showing people’s concern about the announcement. By using the cross-correlation coefficient ρDCCA, we identify strong cross-correlations between the different expressions related to RENCA in Google Trends. Our work shows the utility of Google Trends as an indicator of the perception of environmental policies. Additionally, we show that ρDCCA can be used as a tool to measure the cross-correlation between synonyms extracted from Google Trends for various time scales.

The Tianlai dish array low-z surveys forecasts

ABSTRACT We present the science case for surveys with the Tianlai dish array interferometer tuned to the [1300, 1400] MHz frequency range. Starting from a realistic generation of mock visibility data according to the survey strategy, we reconstruct maps of the sky and perform foreground subtraction. We estimate the level of residuals from imperfect subtraction, mostly due to mode mixing, i.e. distortions in the reconstructed 3D maps due to frequency-dependent instrument response. We show that a survey of the North Celestial Polar cap during a year of observations, covering an area of $150 \, \mathrm{deg^2}$, would reach a sensitivity of $1.5-2 \, \mathrm{mK}$ per $1 \, \mathrm{MHz} \times 0.25^2 \, \mathrm{deg^2 }$ voxel and be marginally impacted by mode mixing. Tianlai would be able to detect ∼10 nearby massive H i clumps as well as a very strong cross-correlation signal of 21 cm intensity maps with the North Celestial Cap Survey optical galaxies. We also studied the performance of a mid-latitude survey, covering $\sim 1500 \, \mathrm{deg^2}$ overlapping the SDSS footprint. Despite a higher noise level for the mid-latitude survey, as well as significant distortions due to mode mixing, Tianlai would be able to detect a highly significant cross-correlation between the 21 cm signal and the Sloan spectroscopic galaxy sample. Using the extragalactic signals measured from either or both of these surveys, and comparing them with simulations such as those presented here will make it possible to assess the impact of various instrumental imperfections on the Tianlai dish array performance. This would pave the way for future intensity mapping surveys with higher sensitivity.

Did Schwabe cycles 19–24 influence the ENSO events, PDO, and AMO indexes in the Pacific and Atlantic Oceans?

The sea surface temperature (SST), anomalies (SSTA), Oceanic Niño Index (ONI), and Multivariate ENSO (MEI) index in El Niño 1 + 2 and El Niño 3.4 regions, Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO), as well as the meteorological parameter Southern Oscillation Index (SOI) were cross correlated to sunspot counts (SS) from cycles 19 to 24 (1954–2019). Over the 1954–2019 period, the SS or Schwabe cycles did not show strong cross-correlation coefficients (cc-ρ) with values falling between 0.063 and 0.100 ( p < 0.05). It seems that the Total Solar Irradiation (TSI) constant variability (±0.1%, ±1.361 W m −2 ) due to the SS cycles balanced out throughout the whole period. The cc-ρ coefficients for SST and SSTA versus each individual SS cycles were between 0.100 and 0.200 with lag times between maxima of each being from a few to 48 months. The ONI showed a cc-ρ < 0.1, while MEI reached up to 0.2 through all SS cycles. The slope of the cc-ρ changed from negative to positive over 6–12 months periods, with peaks in slope change occurring somewhere between 2 and 3 years. The SOI cc-ρ varied by around 0.200 through cycles 19–21, but for SS 22–24 it was not noticeable. Interdecadal indexes PDO and AMO showed cc-ρ of up to 0.283; with a possible association of 8%, with a lag time of 1–3 years. During the ascending and descending phases of each SS cycle, the cc-ρ were 0.288 and − 0.233, respectively for SST in El Niño 3.4 region, but in El Niño 1 + 2 were negligible. The ONI and MEI showed cc-ρ up to 0.448 and 0.480 respectively with lag times of 1–15 months in ascending phase of the SS cycle. The SS vs SOI had cc- ρ up to +0.420 to −0.567 in the ascending phases, while PDO and AMO registered cc-ρ up to 0.417 and − 0.491. AMO appeared systematically associated with SS cycles from 10.0 to 30.2% during descending and ascending phases, respectively. Compiled SS counts for all the ascending and descending phases of the SS cycles, gave a clear spectral coherence (quasi sine-function distribution); for SST and SSTA, lag times of 9–48 months were observed with inverse and direct linear relationship, and peaks of −0.38 and 0.39, respectively. The ONI and MEI with SS counts have similar cc-ρ values: 0.245 and 0.387. Around 6–15% of the ONI and MEI can be explained by SS during ascending and < 4% in descending phases. It seems that over the relatively short time scales of SS cycles, either on their initial ascending or final descending phases, the studied indexes seem to be influenced. Even though it was difficult to elucidate the physics behind the observed cross-correlations, these results can be used to help improve understanding and aid the predictions of ENSO, PDO and AMO oceanographic events in the Pacific and Atlantic oceans. • Sea surface temperature is affected by sun energy that varies in time due to astronomical factors and sun internal activity • The sun activity can be estimated by sun spots (SS) • Inter-annual El/La Niño/Niña as well as decadal processes should be affected by SS • It was found weak to moderate cross-correlation between SS and oceanographic indexes from 1954 to 2019 • This fact should be considered to improve skill modelling forecasts of such indexes

Cross-correlation effects in the solution NMR spectra of near-equivalent spin-1/2 pairs.

The nuclear magnetic resonance (NMR) spectra of spin-1/2 pairs contain four peaks, with two inner peaks much stronger than the outer peaks in the near-equivalence regime. We have observed that the strong inner peaks have significantly different linewidths when measurements were performed on a 13C2-labelled triyne derivative. This linewidth difference may be attributed to strong cross-correlation effects. We develop the theory of cross-correlated relaxation in the case of near-equivalent homonuclear spin-1/2 pairs, in the case of a molecule exhibiting strongly anisotropic rotational diffusion. Good agreement is found with the experimental NMR lineshapes.

Experimental Investigation of Fluid-Structure Interaction in Mach 2 Flow Using Simultaneous High-Speed PIV and DIC

The fluid-structure interaction (FSI) of a compliant panel under a compression-ramp-induced shock-wave/boundary-layer interaction (SBLI) has been studied in Mach 2 flow. Simultaneous high-speed measurements of the velocity field and the panel displacement were conducted using 50 kHz particle image velocimetry (PIV) and 5 kHz stereoscopic digital image correlation (DIC). The mean effect of the panel displacement has been evaluated by monitoring the change in velocity profiles along the streamwise direction (x), upstream of the separated flow region. Streamwise (u) velocity near the panel surface has been shown to change its magnitude in response to the wall shape. Furthermore, the strong cross-correlation between fluctuations of the wall-normal panel displacement and the transverse (v) velocity can be explained by the flow remaining tangent to the wall surface as the panel deforms. This latter result is consistent with the panel motion being sufficiently low frequency compared to flow convective time scales that the flow is quasi-steady. In addition, assessment of the correlation between the separation shock position and panel displacement seems to suggest that when the panel is bulged down (concave up) at the downstream end of the panel, a larger separated flow is generated and the shock moves upstream. This observation remains speculative, but is consistent with the flow undergoing greater compression for the bulged down case.