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• New S L experiment of CH 4 flames diluted by N 2 /AR/CO 2 covering unexplored conditions. • Linear ln S L vs. 1 Y u relationships across N 2 , CO 2 , H 2 O, AR, and HE diluted flames. • Validity of the correlation for multiple-diluent conditions in real applications. • Mathematical fitted results provided for the engineering usage. • Linear dT dx max vs. f and HRR max vs. f 2 dependences offer insight for flame analysis. Introducing diluents is a typical technique in the modern combustion process to control pollutant emissions. While extensive research in literature has explored the inerting effects of different diluents on the CH 4 flame laminar burning velocities through experiments and numerical simulations, applying these findings directly to real applications is often impractical. A more efficient approach is the utilization of correlation equations. This study validates a linear correlation proposed in our former work (Fuel 2024;364:131108) for the CH 4 flames diluted by N 2 , CO 2 , H 2 O, Ar, and He. Laminar burning velocities of CH 4 + O 2 + N 2 , CH 4 + O 2 + Ar, and CH 4 + O 2 + CO 2 flames under varying diluent types, dilution ratios, and equivalence ratios were measured by the heat flux method at 1 atm and 298 K to provide precise validation data. Simulations were also conducted using four recently published mechanisms. The experimental and simulation results demonstrate strong linearity in the proposed correlation for CH 4 + O 2 flames diluted by N 2 , CO 2 , H 2 O, Ar, and He, regardless of equivalence ratios. Furthermore, considering real applications such as exhaust gas recirculation, the study also validates the correlation's applicability under conditions involving multiple diluents. To facilitate practical engineering applications, mathematically fitted results of the correlation equations for single and multiple diluents are provided in both mass- and mole-based units. [ABSTRACT FROM AUTHOR]

Amantadine, an antiviral drug, has been widely used in human anti‐influenza treatments. However, several highly pathogenic avian influenza viruses show amantadine‐resistance mutations in the viral matrix 2 (M2) protein. Here we analyzed global H5N1 sequencing data and calculate possible correlations between frequencies of key mutations in M2 and the mortality rates. We found that the frequency of L26I/V27A mutation in M2 (isolated from both human and avian hosts) is linearly correlated with the mortality rates of human H5N1 infections. The significant correlation between M2 mutations in avians and the mortality rates in humans suggests that the pre‐existence of L26I/V27A in birds may determine patient fatalities after transinfections from avian to human hosts. 100% prevalence of L26I/V27A mutation increased the mortality rates from 51% (95% confidence interval [CI] 37%–65%) to 89% (95% CI 88%–90%). Mutations involving Leu26 or Val27 were identified to be the major mutations emerging from drug selection pressure. Thus the emergence of the super H5N1 virus with a fatality of over 90% may be attributed to the abuse of amantadine in poultry, especially in some southeast Asian countries. A more stringent control to antiviral veterinary drugs is imperative. Highlights: Highly pathogenic H5N1 viruses show amantadine‐resistance mutations in M2 protein.The frequency of L26I/V27A mutation in M2 is linearly correlated with mortality rates.Pre‐existence of L26I/V27A in birds may determine the fatalities in humans.Frequencies of mutations in PB2 and NA were not correlated with the mortality rate.The H5N1 virus with a fatality of over 90% may be attributed to the abuse of amantadine in poultry. [ABSTRACT FROM AUTHOR]

The partial current densities of forming CH 4 and C 2 products in electrocatalytic CO 2 reduction exhibit a linear correlation over a wide potential range, and the slope can be well tuned by different Cu-based catalysts. [Display omitted] Although many catalysts have been reported for the CO 2 electroreduction to C 1 or C 2 chemicals, the insufficient understanding of fundamental correlations among different products still hinders the development of universal catalyst design strategies. Herein, we first discover that the surface *CO coverage is stable over a wide potential range and reveal a linear correlation between the partial current densities of CH 4 and C 2 products in this potential range, also supported by the theoretical kinetic analysis. Based on the mechanism that *CHO is the common intermediate in the formation of both CH 4 (*CHO → CH 4) and C 2 (*CHO + *CO → C 2), we then unravel that this linear correlation is universal and the slope can be varied by tuning the surface *H or *CO coverage to promote the selectivity of CH 4 or C 2 products, respectively. As proofs-of-concept, using carbon-coated Cu particles, the surface *H coverage can be increased to enhance CH 4 production, presenting a high CO 2 -to-CH 4 Faradaic efficiency ( FE CH 4 ∼52%) and an outstanding CH 4 partial current density of –337 mA cm−2. On the other hand, using an Ag-doped Cu catalyst, the CO 2 RR selectivity is switched to the C 2 pathway, with a substantially promoted FE C 2 of 79% and a high partial current density of –421 mA cm−2. Our discovery of tuning intermediate coverages suggests a powerful catalyst design strategy for different CO 2 electroreduction pathways. [ABSTRACT FROM AUTHOR]

Twenty-five numbers of O-H···N≡C H-bonded complexes formed between 5 alcohols and 5 nitrile compounds have been studied using IR spectroscopy in room temperature CCl4 solution to elucidate the impact of donor alcohols on the ν C ≡ N and ν O − H spectral shifts. The magnitude of blue and red shifts exhibited by ν C ≡ N and ν O − H , respectively, upon H-bond formation were found to show an orderly trend with varying H-bond donor; both types of spectral shifts showed a linear dependence on the p K a of the alcohols. Besides, it was also found that both Δ ν C ≡ N and Δ ν O − H show a linear correlation between themselves. Quantum chemical calculations carried out at B97D/6-311++G(d,p) level of theory corroborated the experimental results. H-Bond distance scans were also performed to look at the effect of H-bond distance on spectral shift. Furthermore, AIM and NBO analyses have also been performed to support the results. The findings have been compared against 25 numbers of O-H···O=C H-bonded complexes formed between the same 5 alcohols and 5 carbonyl compounds, both experimentally and theoretically. Unlike the red- and blue-shifted donors, different counterpropagating forces were also found to act simultaneously in the case of acceptors to govern the nature of shift. [ABSTRACT FROM AUTHOR]

In many real-world applications, the phenomena of interest are continuous in nature and modeled through continuous probability distributions, but their observed values are actually discrete and hence it would be more reasonable and convenient to choose an appropriate (multivariate) discrete distribution generated from the underlying continuous model preserving one or more important features. In this paper, two methods are discussed for deriving a bivariate discrete probability distribution from a continuous one by retaining some specific features of the original stochastic model, namely (1) the joint density function, or (2) the joint survival function. Examples of applications are presented, which involve two types of bivariate exponential distributions, in order to illustrate how the discretization procedures work and show whether and to which extent they alter the dependence structure of the original model. We also prove that some bivariate discrete distributions that were recently proposed in the literature can be actually regarded as discrete counterparts of well-known continuous models. A numerical study is presented in order to illustrate how the procedures are practically implemented and to present inferential aspects. Two real datasets, considering correlated discrete recurrence times (the former) and counts (the latter) are eventually fitted using two discrete analogues of a bivariate exponential distribution. [ABSTRACT FROM AUTHOR]

Recognition of a brain region's interaction is an important field in neuroscience. Most studies use the Pearson correlation to find the interaction between the regions. According to the experimental evidence, there is a nonlinear dependence between the activities of different brain regions that is ignored by Pearson correlation as a linear measure. Typically, the average activity of each region is used as input because it is a univariate measure. This dimensional reduction, i.e., averaging, leads to a loss of spatial information across voxels within the region. In this study, we propose using an information-theoretic measure, multivariate mutual information (mvMI), as a nonlinear dependence to find the interaction between regions. This measure, which has been recently proposed, simplifies the mutual information calculation complexity using the Gaussian copula. Using simulated data, we show that the using this measure overcomes the mentioned limitations. Additionally using the real resting-state fMRI data, we compare the level of significance and randomness of graphs constructed using different methods. Our results indicate that the proposed method estimates the functional connectivity more significantly and leads to a smaller number of random connections than the common measure, Pearson correlation. Moreover, we find that the similarity of the estimated functional networks of the individuals is higher when the proposed method is used. [ABSTRACT FROM AUTHOR]

Urea electrosynthesis under mild conditions starting from the adsorption of inert N2 molecules has brought out a promising alternative experimentally to conquer its huge energy consumption in industrial Haber‐Bosch process. The most crucial and inevitable reaction is the formation of urea precursor *NCON from *N2 and CO based on the pre‐selected reaction pathway, together with the following protonated processes. It is significant to comprehend their intrinsic intercorrelation and explore the principal descriptor from massive reaction data. Hereby, the authors study the dispersed dual‐metals (homonuclear MN3–MN3 moiety and heteronuclear MN3–M'N3 moiety) anchored on N‐doped graphene as electrocatalysts to synthesize urea. Based on the screened out 72 stable systems by ab initio molecular dynamics (AIMD) simulations as the database, six significant linear correlations between the computed Gibbs free energy and other important factors are achieved. Most encouragingly, the principal descriptor (ΔE(*NCONH)) is established because 72% low‐performance systems can be filtered out and its effective range (−1.0 eV < ΔEE(*NCONH) < 0.5 eV) is identified by eight optimal systems. This study not only suggests that dispersed dual‐metals via MN3 moiety can serve as promising active sites for urea production, but also identifies the principal descriptor and its effective range in high‐throughput methods. [ABSTRACT FROM AUTHOR]

Molecule rotation in the control of fungal diseases is essential to ensure sustainability and avoid the tolerance of pathogens to fungicides. Evidencing managements that promote greater efficiency in the control can contribute to increase the efficiency in the control of diseases. This work aims to reveal control alternatives for foliar diseases through different anti-fungal molecules applied in pre-flowering in the linseed crop. The experiment took place in the experimental area of Escola Fazenda, UNIJUÍ, located in the municipality of Augusto Pestana (RS). The experimental design used randomized blocks, with ten fungicide treatments in foliar application and three replications, totaling 30 experimental units. In the useful area of each experimental unit, the following characteristics were measured: plant height, plants per square meter, number of grains per plant, weight of grains per plant, grain yield, normalized green red difference index, green leaf index, spectral saturation index. The data obtained were submitted to descriptive analysis and to the assumptions of analysis of variance, such as homogeneity of residual variances by Bartlett's test and normality of errors by Shapiro Wilk. Afterwards, analysis of variance was carried out at 5% probability, with the significant variables, Tukey's test of multiple comparison of means was applied at the level of 5% of probability. In order to identify the tendency of association between the characters, Pearson's linear correlation was determined at 5% probability by t test. The active ingredient Pyraclostrobin + Fluxapyroxad can contribute favorably to the maintenance of floral units, capsules and grains per plant. The correct positioning of the use of the molecule is decisive and requires further studies in linseed culture. [ABSTRACT FROM AUTHOR]

Abstract MGMT-promoter methylation is associated with favorable outcome in glioblastoma. The aim of this study was to determine whether the absolute number of methylated Cytosine-Guanine-dinucleotide-(CpG-)sites within the DMR-2 island of the MGMT-promoter may correlate with outcome in a qualitative or quantitative fashion. In a cohort of newly diagnosed glioblastoma patients treated with stereotactic biopsy or open tumor resection plus concomitant chemoradiotherapy, we assessed MGMT-promoter methylation by methylation-specific polymerase-chain-reaction (MSP). Methylation of the CpG-sites 74–98 within the MGMT-promoter region was additionally analysed by Sanger sequencing, and the total number of methylated CpG-sites was correlated with outcome using proportional hazards models. 215 patients with glioblastoma were identified and stratified per MSP (positive: 53%, negative: 47%). Among MSP-positive tumors, hierarchical clustering identified three subgroups with different methylation rates (median: 80% vs. 52% vs. 47%), indicating a site-dependent methylation propagation. The methylation status of a given CpG-site indicated a neighborhood-dependent methylation propagation. Survival was linearly associated with the cumulative number of methylated CpG-sites. This was particularly true in patients who received at least one adjuvant cycle of temozolomide. Notably, all CpG-sites analyzed contributed similarly to effect size; this enabled a further predictive substratification of MSP-positive tumors with median OS ranging from as low as 17.1 months (

Many properties of starch-containing foods are significantly statistically correlated with various structural parameters. The significance of a correlation is judged by the p-value, and this evaluation is based on the assumption of linear relationships between structural parameters and properties. We here examined the linearity assumption to see if it can be used to predict properties at conditions that are not close to those under which they were measured. For this we used both common domesticated rices (DRs) and Australian wild rices (AWRs), the latter having significantly different structural parameters and properties compared to DRs. The results showed that (1) the properties were controlled by more than just the amylopectin or amylose chain-length distributions or amylose content, other structural features also being important, (2) the linear model can predict the enthalpy ΔHg of both AWRs and DRs from the structural parameters to some extent but is often not accurate; it can predict the ΔHg of indica rices with acceptable accuracy from the chain length distribution and the amount of longer amylose chains (degree of polymerization > 500), and (3) the linear model can predict the stickiness of both AWRs and DRs to acceptable accuracy in terms of the amount of longer amylose chains. Thus, the commonly used linearity assumption for structure-property correlations needs to be regarded circumspectly if also used for quantitative prediction.

Abstract Urea electrosynthesis under mild conditions starting from the adsorption of inert N2 molecules has brought out a promising alternative experimentally to conquer its huge energy consumption in industrial Haber‐Bosch process. The most crucial and inevitable reaction is the formation of urea precursor *NCON from *N2 and CO based on the pre‐selected reaction pathway, together with the following protonated processes. It is significant to comprehend their intrinsic intercorrelation and explore the principal descriptor from massive reaction data. Hereby, the authors study the dispersed dual‐metals (homonuclear MN3–MN3 moiety and heteronuclear MN3–M'N3 moiety) anchored on N‐doped graphene as electrocatalysts to synthesize urea. Based on the screened out 72 stable systems by ab initio molecular dynamics (AIMD) simulations as the database, six significant linear correlations between the computed Gibbs free energy and other important factors are achieved. Most encouragingly, the principal descriptor (ΔE(*NCONH)) is established because 72% low‐performance systems can be filtered out and its effective range (−1.0 eV < ΔEE(*NCONH) < 0.5 eV) is identified by eight optimal systems. This study not only suggests that dispersed dual‐metals via MN3 moiety can serve as promising active sites for urea production, but also identifies the principal descriptor and its effective range in high‐throughput methods.

Because of the large-scale impact of COVID-19 on human health, several investigations are being conducted to understand the underlying mechanisms affecting the spread and transmission of the disease. The present study aimed to assess the effects of selected environmental factors such as temperature, humidity, dew point, wind speed, pressure, and precipitation on the daily increase in COVID-19 cases in Mississippi, USA, during the period from January 2020 to August 2021. A machine learning model was used to predict COVID-19 cases and implement preventive measures if necessary. A statistical analysis using Python programming showed that the humidity ranged from 56% to 78%, and COVID-19 cases increased from 634 to 3546. Negative correlations were found between temperature and COVID-19 incidence rate (−0.22) and between humidity and COVID-19 incidence rate (−0.15). The linear regression model showed the model linear coefficients to be 0.92 and −1.29, respectively, with the intercept being 55.64. For the test dataset, the R2 score was 0.053. The statistical analysis and machine learning show that there is no linear dependence of temperature and humidity with the COVID-19 incidence rate. [ABSTRACT FROM AUTHOR]

Copyright infringement is a serious problem in the music industry, especially for Internet-based platforms. The existing audio watermarking methods for copyright protection have limited robustness against the desynchronization attacks. Besides, most of the methods are not designed for stereo signals, which are widely used by online-based music and video platforms. In this paper, we present a desynchronization-attack-resilient watermarking method for stereo signals. In the watermark embedding process, both the left channel and the right channel of the host signal are firstly segmented and transformed into the frequency domain using the discrete cosine transform (DCT). Secondly, the linear correlation between channels (LCBC) in the DCT domain is calculated using the Pearson correlation coefficient (PCC). Then watermark bits are embedded by modifying LCBC for each segment. Since the desynchronization attacks as well as other common attacks affect both the left channel and the right channel in a similar manner, LCBC is robust against both desynchronization attacks and other common attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Extreme drought events have caused extensive and severe impacts on terrestrial ecosystem in last decades in China. Given droughts may be more intense and frequent under future climate change, accurate assessment of the drought impact on vegetation primary production can provide reliably scientific supports for the carbon sink potential. Numerous existing studies have used Standardized Precipitation Evapotranspiration Index (SPEI) to discover the drought-production relationships, however, most of them just considered the strongest correlation between production and different time scales (i.e. correlation-based method), which may underestimate the production loss because of the asymmetric responses under dry and wet conditions. In this work, we proposed a new method which assumed that the dominant time scale should correspond to the lowest primary production during each drought year (extreme-based method). Based on six independent Gross Primary Productivity (GPP) products and SPEI dataset, it showed that the extreme-based method was more reasonable and robust (with a larger inter-consistency of 0.50 than that of 0.05 for correlation-based method) to determine at which time scale GPP predominantly responded to extreme droughts. And the GPP loss can be underestimated by 45 ± 26% (mean ± s.d.) if the time scale was randomly selected. Furthermore, spatial analysis suggested that vegetation type, water balance and soil textures mainly affected the spatial heterogeneity of the dominant time scales. In detail, forests, humid biomes, and vegetation planted in loam tended to be more sensitive to longer-term droughts. This study highlighted that optimal time-scale selection using extreme-based assumption can give more accurate estimation of the drought impacts on vegetation primary production.

Background: Pulse interval is a biomarker of psychological and physiological health. Pulse interval can now be assessed using mobile phone apps, which expands researchers' ability to assess pulse interval in the real world. Prior to implementation, measurement accuracy should be established., Objective: This investigation evaluated the validity of the Light Heart mobile app to measure pulse interval and pulse rate variability in healthy young adults., Methods: Validity was assessed by comparing the pulse interval and SD of normal pulse intervals obtained by Light Heart to the gold standard, electrocardiogram (ECG), in 14 young healthy individuals (mean age 24, SD 5 years; n=9, 64% female) in a seated posture., Results: Mean pulse interval (Light Heart: 859, SD 113 ms; ECG: 857, SD 112 ms) demonstrated a strong positive linear correlation (r=0.99; P<.001) and strong agreement (intraclass correlation coefficient=1.00, 95% CI 0.99-1.00) between techniques. The Bland-Altman plot demonstrated good agreement for the mean pulse interval measured with Light Heart and ECG with evidence of fixed bias (-1.56, SD 1.86; 95% CI -5.2 to 2.1 ms), suggesting that Light Heart overestimates pulse interval by a small margin. When Bland-Altman plots were constructed for each participant's beat-by-beat pulse interval data, all participants demonstrated strong agreement between Light Heart and ECG with no evidence of fixed bias between measures. Heart rate variability, assessed by SD of normal pulse intervals, demonstrated strong agreement between techniques (Light Heart: mean 73, SD 23 ms; ECG: mean 73, SD 22 ms; r=0.99; P<.001; intraclass correlation coefficient=0.99, 95% CI 0.97-1.00)., Conclusions: This study provides evidence to suggest that the Light Heart mobile app provides valid measures of pulse interval and heart rate variability in healthy young adults., (©Stephen A Klassen, Jesica Jabbar, Jenna Osborne, Nathaniel J Iannarelli, Emerson S Kirby, Deborah D O'Leary, Sean Locke. Originally published in JMIR Formative Research (https://formative.jmir.org), 20.08.2024.)

Amplified by the development of new technologies, the interest in personal performance has been growing over the last years. Acceleration has proved to be an easy variable to collect, and was addressed in several works. However, few of them evaluate the effect of running speed on relevant indicators. The influence of the sensors location on the measurement is rarely studied as well. This study is dedicated to investigating the effect of running speed on acceleration measured at three different positions on 18 volunteers. All participants were equipped with three inertial measurement units: on the dorsal surface of the right foot (Fo), at the centre of gravity of the tibia (Ti), at the L4-L5 lumbar (Lu). The test was performed on a treadmill at nine randomised speeds between 8 and 18 km/h. Ten accelerometric variables were calculated. Linear regressions were used to calculate speed from the indicators calculated on (Lu), (Ti), (Fo). Indicators associated to signal energy were highly correlated with speed ( r 2 > 0.90). Median frequency appears to be affected by the frequency resolution. Finally, the measurement points closest to the impact zone result in the most correlated indicators. [ABSTRACT FROM AUTHOR]

The Pistacia terebinthus L., is a species belonging to the family Anacardiaceae; a deciduous plant growing in the matorrals, common throughout the Mediterranean basin. The region of Tlemcen, an integral part of Mediterranean ecosystems, is characterized by several climatic and anthropic constraints that can influence the morphology of plant species. Following these constraints and recordings of some phenotypic variations in the station of Beni Snous, it seemed to us that there could be a new species or variety. The sampling adopted is of subjective type by taking into account the floristic homogeneity and the ecological homogeneity of the station. The choice of the station of Beni Snous was justified by the presence of good subjects of Pistacia terebinthus L. he most representative of the study area. In order to meet our objective, the morphometric analysis was performed on the leaves of 16 individuals, that is to say a total of 1126 leaves and 7837 leaflets measured. The statistical analysis of linear correlation, showed us the types of relationships that exist between the measured parameters. According to our results the length of the leaflets is between 3.3 cm and 4.93 cm and the width between 1.38 cm and 2.43 cm; and the number of leaflets in a leaf is on average between 5 and 11 leaflets. In conclusion, according to the analysis and the synthesis of our results of measurements on the one hand, and the comparison with the bibliography on the other hand, we confirmed that it is the same species. [ABSTRACT FROM AUTHOR]

Copyright of Iranian Journal of Range & Desert Research is the property of Research Institute of Forests & Rangelands and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Flue dust from blast furnace is being regularly analysed in the Chemical Laboratory at Tata Steel Plant at Jamshedpur. The analysis includes determination of carbon by combustion-infrared technique, loss on ignition (LOI) at 1000°C and analysis of other constituents such as iron oxide (Fe2O3), lime (CaO), silica (SiO2), phosphorus (P), alumina (Al2O3), magnesium oxide (MgO) and manganese oxide (MnO). The period for determination of carbon and other constituents is usually around 15–20 min, whereas LOI determination takes about 2 h, thus creating an unavoidable delay in reporting the results to the customer. The present study provides an interesting scientific solution to avoid this delay by establishing a strong linear correlation between carbon (≈6.96–45%) and LOI (≈ 4.0–52.0%) values. The study also indicates that the carbon in the flue dust is from the carbonaceous matter fed to the furnace and not due to the fluxes introduced in the furnace during the charging because no correlation was observed between the carbon values and CaO, MgO values of flue dust. This correlation obtained is further proved with the help of characterisation techniques such as X-ray diffraction (XRD), Fourier transform infrared analysis (FTIR) and Raman analysis. [ABSTRACT FROM AUTHOR]

Residual displacement spectrum is one of the most important means to predict the permanent deformation of structures after the earthquake, and various normalizations of residual displacements have generally been used for construction of the spectrum. However, the issue regarding the merits and drawbacks of each normalization has not yet been investigated thoroughly. A comparison between two normalizations that relate the residual displacements to the elastic and inelastic displacements is made in terms of the effect of ground motion and structural characteristics by means of the results of nonlinear time history analysis. The statistical results reveal that the residual-to-peak-inelastic displacement ratios have the advantages of small dispersion, samples without any outliers, and relatively symmetric distribution, which benefits from the strong correlation between residual and peak inelastic displacements. Moreover, the residual-to-peak-inelastic displacement ratios are almost independent of site conditions, significant duration, and natural periods. Consequently, the peak inelastic displacements are superior to the elastic ones as an intermediate step for residual displacements estimation, provided that the peak inelastic displacements are estimated with a low uncertainty. For providing alternatives to estimate residual displacement demands, the constant-strength residual displacement spectra are developed for both normalizations. [ABSTRACT FROM AUTHOR]

Recognition of a brain region’s interaction is an important field in neuroscience. Most studies use the Pearson correlation to find the interaction between the regions. According to the experimental evidence, there is a nonlinear dependence between the activities of different brain regions that is ignored by Pearson correlation as a linear measure. Typically, the average activity of each region is used as input because it is a univariate measure. This dimensional reduction, i.e., averaging, leads to a loss of spatial information across voxels within the region. In this study, we propose using an information-theoretic measure, multivariate mutual information (mvMI), as a nonlinear dependence to find the interaction between regions. This measure, which has been recently proposed, simplifies the mutual information calculation complexity using the Gaussian copula. Using simulated data, we show that the using this measure overcomes the mentioned limitations. Additionally using the real resting-state fMRI data, we compare the level of significance and randomness of graphs constructed using different methods. Our results indicate that the proposed method estimates the functional connectivity more significantly and leads to a smaller number of random connections than the common measure, Pearson correlation. Moreover, we find that the similarity of the estimated functional networks of the individuals is higher when the proposed method is used.

MGMT-promoter methylation is associated with favorable outcome in glioblastoma. The aim of this study was to determine whether the absolute number of methylated Cytosine-Guanine-dinucleotide-(CpG-)sites within the DMR-2 island of the MGMT-promoter may correlate with outcome in a qualitative or quantitative fashion. In a cohort of newly diagnosed glioblastoma patients treated with stereotactic biopsy or open tumor resection plus concomitant chemoradiotherapy, we assessed MGMT-promoter methylation by methylation-specific polymerase-chain-reaction (MSP). Methylation of the CpG-sites 74–98 within the MGMT-promoter region was additionally analysed by Sanger sequencing, and the total number of methylated CpG-sites was correlated with outcome using proportional hazards models. 215 patients with glioblastoma were identified and stratified per MSP (positive: 53%, negative: 47%). Among MSP-positive tumors, hierarchical clustering identified three subgroups with different methylation rates (median: 80% vs. 52% vs. 47%), indicating a site-dependent methylation propagation. The methylation status of a given CpG-site indicated a neighborhood-dependent methylation propagation. Survival was linearly associated with the cumulative number of methylated CpG-sites. This was particularly true in patients who received at least one adjuvant cycle of temozolomide. Notably, all CpG-sites analyzed contributed similarly to effect size; this enabled a further predictive substratification of MSP-positive tumors with median OS ranging from as low as 17.1 months (< 18 methylated CpG-sites) to as high as 26.2 months (≥ 18 methylated CpG-sites) in the overall cohort. All in all, total number of methylated CpG-sites may correlate with outcome in a linear fashion. Such analysis may therefore add further predictive value to conventional methods of determining the MGMT-promoter status. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for introductory teaching of the sample linear correlation coefficient from a bivariate dataset. Linear correlation is typically included in curriculums at the secondary and introductory tertiary levels of education. The method discussed herein can be used by educators in elementary courses at either of these levels. We explain how scatterplots with the addition of contour plots can be used to teach the strength and direction of linear relationship between two variables; and demonstrate the production of contour plots using statistical computing software. Finally, we show how this innovative method could be included in classroom activities. [ABSTRACT FROM AUTHOR]

Copyright of Comunicaciones en Estadística is the property of Universidad Santo Tomas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Because of the large-scale impact of COVID-19 on human health, several investigations are being conducted to understand the underlying mechanisms affecting the spread and transmission of the disease. The present study aimed to assess the effects of selected environmental factors such as temperature, humidity, dew point, wind speed, pressure, and precipitation on the daily increase in COVID-19 cases in Mississippi, USA, during the period from January 2020 to August 2021. A machine learning model was used to predict COVID-19 cases and implement preventive measures if necessary. A statistical analysis using Python programming showed that the humidity ranged from 56% to 78%, and COVID-19 cases increased from 634 to 3546. Negative correlations were found between temperature and COVID-19 incidence rate (−0.22) and between humidity and COVID-19 incidence rate (−0.15). The linear regression model showed the model linear coefficients to be 0.92 and −1.29, respectively, with the intercept being 55.64. For the test dataset, the R2 score was 0.053. The statistical analysis and machine learning show that there is no linear dependence of temperature and humidity with the COVID-19 incidence rate.

The new technological advances have brought a revolution on how economic agents interact with society and markets. Nowadays, the use of virtual currencies is more frequent in the financial transactions and bitcoin has been defined as the most important world cryptocurrency due to its high market capitalization and its technological infrastructure. Several studies have been conducted to discuss bitcoin advantages and disadvantages; however, few papers in literature have examined its connection and influence on the stock market. The objective of this paper is precisely cover this gap. Firstly, by providing tools and concepts to understand bitcoin’s dynamic, and then determining its relationship with stock market indexes. In that context, this manuscript examines the definition and function of bitcoin in the global world and its presence in Ecuador. Besides, exploratory and visual analyses are provided using the evolution of bitcoin and other market indexes. Finally, a linear correlation is computed between bitcoin, other cryptocurrencies, stock exchange indexes and commodities. The results in this study, employing visual and statistical analyses, demonstrated that bitcoin has: a strong relationship with other cryptocurrencies; a lineal correlation, not as strong as the previous one, with the main stock market indexes; and no linear correlation with commodities.

Traditional coherence algorithms are mostly based on the assumption that seismic traces are Gaussian and linear correlative. However, for nonGaussian seismic traces, the linear correlation analysis cannot accurately describe the similarity between adjacent seismic traces. To solve this issue, we adopt the kernel correlation instead of the linear correlation to improve coherence-based algorithms. Note that the kernel correlation is a generalized correlation with various kernel functions. It provides a framework for expanding the coherence algorithm based on linear correlation. Moreover, we discuss how to choose an appropriate kernel function in detail. To testify the validity of the kernel correlation, we apply it to field data using different kernels. The results demonstrate the effectiveness of the proposed algorithm to describe geological discontinuity and heterogeneity, such as fluvial channels and faults. [ABSTRACT FROM AUTHOR]

A pilot-scale horizontal subsurface flow constructed wetland (HFCW) was established to investigate the feasibility of removing nutrients from natural water in Lake Xijiu, Jiangsu Province, China. The HFCW, planted with reeds (Phragmites communis) and irises (Iris tectorum Maxim), was operated for 227 days. The mean removal efficiency of NH4+-N was 36.7%, of total nitrogen (TN) 70.2%, of total phosphorus 75.3%, of permanganate index (CODMn) 35.8%, and of Chlorophyll a 70.0%. The effluent concentrations of these pollutants were all within the Grade III threshold of China's water quality standards for surface water. Correlation analysis showed that TN removal was related to the CODMn concentration in the influent (r2 = 0.65) and was closely related to the temperature (r2 = 0.91). The HFCW had a water production efficiency of 98%–99% over the entire operational period, which suggests that it did not block easily. Results from 16S rDNA high-throughput sequencing showed that Proteobacteria (40.65%) dominated at the phylum level. At the genus level, the relative abundance of Nitrosomonadaceae (3.57%) was highest in autumn and the spatial distribution from the front to the back varied slightly from 2.57% to 2.99%. Our results will help researchers to develop optimal designs for HFCW systems to treat slightly polluted water. [ABSTRACT FROM AUTHOR]

Fatty acids are the major compounds in olive oils, and the determination of their profile is very useful in order for the authentication of the high quality of extra virgin olive oil (EVOO) and the evaluation of its purity and traceability. This work considers the estimations of saturated (SAFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids obtained by gas chromatography (GC), 13C (carbonyl, C‐16, and aliphatic carbons regions), and 1H NMR spectra. The aim of this paper is to analyze the correlation structure being between the abovementioned fatty acids estimations and some long‐run agroclimatic measurements (temperature, humidity, wind speed and direction, radiation, precipitation, and evapotranspiration), which were downloaded from the official website of the Andalusian Automatic Weather Stations (AWSs). The versatile graphical possibilities of the free software R‐project allow the design of computational programs providing interesting conclusions about the described correlations as a function of month, variety of olive, and protected designation of origin (PDO). The statistically significant correlations could determine relevant agroclimatic information to be included, in a further research, among the explanatory variables in regression models in order to improve the estimation of fatty acid profile of EVOOs, considered as a quality parameter in their authentication. Fatty acids are the major compounds in olive oils and very useful in order to the authentication of the high quality of extra virgin olive oil (EVOO). This paper analyzes the effect of agroclimatic big fata, instead of a meteorological factor, on EVOO fatty acid profile determined by GC and NMR spectra. The power of the free software R‐project and its versatile graphical possibilities allows the design of computational programs providing interesting conclusions about the described correlations as a function of month, variety of olive, and protected designation of origin (PDO). [ABSTRACT FROM AUTHOR]

The objective of this study was to generate information through the analysis of variability and given structure of spatial dependence as well as the linear correlation of physical and chemical attributes of the soil, in order to assist in the planning of agricultural activities in six cities in the province of El Oro, Ecuador. The soil sample collections were carried out every two kilometers in the form of a grid with small changes in the field with a Dutch-type auger and GPS for georeferencing, with a depth of 0-0.20 m, thus totaling 368 points in the sample grid. Chemical and physical attributes of six municipalities in the province of El Oro were evaluated: Huaquillas, Machala, Chilla, Atahualpa, Portovelo and Las Lajas. The sampling was carried out in each city, but not between them. Distances between cities were 20,000 km to 180,000 km. Each soil attribute was subjected to an initial descriptive analysis, geostatistics and simple linear correlation matrix. Only pH and sand showed a high variation coefficient (22.02% and 25.42%) and all other attributes showed very high variation. Most of the semivariograms were adjusted to the spherical model. The longest range was indicated by magnesium (41,500 m) and the shortest by copper (7,740 m). The Mg pair versus sum of bases was the highest linear correlation among all the analyzed attributes. The pH stood out with a greater linear correlation between the other chemical attributes of the soil and its specific management zones. In view of the great taxonomic variation of the soil, climatic types, cultures used and management adopted, a specific analysis in each city is recommended for better agricultural recommendations. [ABSTRACT FROM AUTHOR]

Crystal structure and the optical spectral properties of 0.5 at.% Nd3+, 5 at.% Gd3+‐codoped Ca1‐xSrxF2 (0 ≤ x≤1) crystals grown by the temperature gradient technique (TGT) were investigated. The linear variations of the crystal structure and spectral parameters as a function of Sr2+ proportion (x) were observed and correlated with each other. The results indicated that Sr2+ ions introduced as matrix‐substituted ions could regulate the crystal structures and the spectroscopic properties. [ABSTRACT FROM AUTHOR]

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This paper is devoted to investigate a class of complex chaotic systems and a linear correlation between the real and imaginary component of complex variables in these systems is found. Based on this linear relationship, a simplified law is proposed. First, complex Lorenz system is given to show the linear correlation, then it is simplified. Second, a simplified law is proposed to determine whether the complex system can be simplified, and the complex Lü system and hyperchaotic complex Lü system are used to verify the simplified law. Finally, a new synchronization control is proposed to synchronize complex Lorenz system and real Lorenz system. The theoretical analysis and numerical simulation prove the feasibility and better performance of this method. [ABSTRACT FROM AUTHOR]

The Kjeldahl and combustion (Dumas) methods are the main methods used to determine total nitrogen (TKN and TCN) content in agriculture biomass. However, the results obtained using these methods differ because of differences in their underlying principles. Herein, we used these two methods to determine the total nitrogen content in 1 179 crop residues (rice straw, wheat straw, corn stover, rape stalk, cotton stalk) from China, and systematically analyzed and compared in total nitrogen content and their distributions in the collected crop residues by different types with these two methods. Seven common distributions (Normal, Lognormal, Gamma, Weibull, Exponential, Laplace, Lorentz) were used to determine the data distribution types of TKN and TCN in different crop residues. The correlation between the two methods was explored using ordinary least squares regression (OLS), orthogonal regression (Orth), and least median square regression (LMS). Finally, the research reviewed the correlation between different biomass (food, flowers, grass, soil, crop, crop residues, sewage sludge and animal manure, etc.) results of two methods for measuring nitrogen content. The results showed: The distributions of nitrogen content were non-normal distributions in different crop residues. The total TKN and TCN contents were the same distributions in rice straw, wheat straw, rape stalk and total crop residues which approximately followed Lognormal, Gamma, Lognormal and Lognormal respectively. The median method was recommended for data statistics, and results from low to high were: 1) TKN: wheat straw (5.66 ± 1.07 g/kg), rape stalk (7.10 ± 1.87 g/kg), rice straw (8.20 ± 1.42 g/kg), corn stover (8.82 ± 2.23 g/kg), cotton stalk (10.42 ± 1.45 g/kg); 2) TCN: wheat straw (6.17 ± 1.17 g/kg), rape stalk (8.50 ± 2.45 g/kg), rice straw (8.59 ± 1.45 g/kg), corn stover (10.10 ± 1.91 g/kg), cotton stalk (11.75 ± 1.48 g/kg). It was found that TKN was significantly lower than TCN in all types of crop residues (P < 0.05). TKN and TCN values were also significantly different among wheat straw, cotton stalk and other crop residues (P < 0.05). Although the fitting efficiencies of OLS, Orth and LMS were the same on the determination coefficient (R2) scale, the fitting results were different. LMS was recommended because it reduced the effect of outliers compared with three methods, observed from kernel density – scatter plots. Five types of crop residues and the total had different fitting result between TKN and TCN. The correlation between TKN and TCN for total crop residues was quantified as the LMS equation. In addition, there was a gap of the linear relationships between TKN and TCN in different types of biomass. The slope of plant biomass was generally lower than that of animal manure, whose potential reason was different forms and contents of nitrogen in different biomass (ammonium nitrogen, nitrate nitrogen, nitrite nitrogen, heterocyclic nitrogen, and nucleic acid nitrogen, etc.). The results may provide extensive and reliable data for reference from large sample size, and methods support for the scientific utilization of nitrogen in crop residues. [ABSTRACT FROM AUTHOR]

Based on 5000 analyses of geological prospecting samples from four alunite deposits (Began', Ukraine; Haft Sanduq, Iran; Bolshaya Kremenyukha and Kachar, Kazakhstan) and 6000 microprobe analyses of alunite, the features of changes in three parameters of alunite quartzite composition have been studied: (1) alunite content, (2) mole fraction of K in alunite, and (3) correspondence of the amount of K and Na to that of alunite sulfur. All three parameters are highly variable. A linear correlation between them has been identified in over half of the exploration workings. This correlation is sometimes very strong, approaching a functional relationship, especially for two: the alunite content and mole fraction of K in alunite. In the first three of the above-mentioned deposits, this correlation is almost always positive, and in the last, it is always negative. In other words, as alunite content increases, it becomes higher-K in the first case and higher-Na in the second case. Alunite quartzite makes up a regular zone of the infiltration metasomatic column of sulfuric acid alteration in aluminosilicate rocks under conditions apparently close to isothermal. However, the highly variable contents of the basic minerals (alunite and quartz) and alunite composition point to a difference between the alunite quartzite formation model and the theoretical model for isothermal infiltration metasomatic rock. According to the theoretical model, the solution and rock compositions mainly change at the boundaries of the metasomatic zone, whereas the rock and mineral compositions are not characterized by significant variations within the zone. During alunite quartzite formation, the solution and rock compositions change not only at the boundaries, but also within the zone due to ongoing oxidation of sulfur compounds in the solution with the sulfate formation. An increasing sulfate concentration leads to the solution becoming supersaturated in relation to alunite and causes its precipitation, with filling of voids and displacement of quartz. Cooling, heating, or a change in the composition of the hydrothermal system solutions lead to temporal variations in the K/Na ratio in precipitated alunite. Alunite formation inside the alunite zone, accompanied by changes in the mole fraction of K in deposited alunite, is the reason for the high variability of the alunite quartzite composition and for the correlation between the alunite content and its mole fraction of K. If the contribution of higher-K alunite to the variability of its total content is higher than that of higher-Na alunite, a positive correlation is likely to appear, otherwise a negative correlation is more probable. [ABSTRACT FROM AUTHOR]

A very broad acidity scale (≈40 pK units) for about 400 N‐heterocyclic carbene precursors (NHCPs) with various backbones and electronic features, including imidazolylidenes, 1,2,4‐triazolylidenes, cyclic diaminocarbenes (CDACs), diamidocarbenes (DACs), thiazolylidenes, cyclic (alkyl)(amino)carbenes (CAACs) and mesoionic carbenes (MICs), was established in DMSO by a well examined computational method. Varying the backbone structure or flanking N‐substituents can have different extent of acidifying effects, depending on both the nature and number of substituent(s). The Gibbs energies (ΔGrs) for the reactions between the corresponding NHCs and CO2 were also calculated. There is a good linear correlation between the pKas of most NHCPs and ΔGrs, suggesting that a greater basicity of NHC leads to a more stable NHC‐CO2 adduct. Interestingly, the nearby asymmetric environment has virtually no differential effect on the acidities of the chiral NHCP enantiomers, but has a pronounced effect on the ΔGr values. [ABSTRACT FROM AUTHOR]

• Coupling normalized abundance with ICR can get accurate abundance retrieval model. • The model can enhance the linear relationship between CRBD and mineral abundance. • The model performs better in abundance inversion on synthetic and real image data. • It has potential to extend to survey extraterrestrial minerals. Mapping or quantitatively estimating mineral content using remote sensing technology is an active way for monitoring minerals in large or inaccessible areas. Different spectral features of minerals, induced by their ionic composition, can be identified and related to mineral type or abundance. Based on the distinctive spectral absorption around 2.33 µm induced by the carbonate ion, we propose an improved continuum removal (ICR) algorithm, coupled with normalized abundance, to assess the relationship between continuum removal band depth (CRBD) and carbonate ion abundance. Through experiments using synthetic and real image data, ICR with ratio abundance normalization enhances the linear relationship between CRBD and abundance, resulting in the best performance for abundance retrieval. The synthetic data showed the lowest root mean square error of 0.04, while the lowest mean relative error for real image data reached 6.80 %. Compared it with five other algorithms, coupling normalized carbonate mineral abundance with ICR improves the accuracy of quantitative retrieval of carbonate ion. These results demonstrate that the proposed approach effectively reduces the influence of reflectance differences caused by external factors, providing a more reasonable algorithm to enhance spectral absorb features and quantitatively retrieve mineral abundance. The proposed approach has the potential to extend mineral information extraction even in the absence of sample data, and can be applied in surveys of the Moon and Mars for mineral quantitative analysis. [ABSTRACT FROM AUTHOR]

Introduction: Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obligatory for graph construction and analysis is consistently underestimated by LC, because not all the bivariate distributions, but only the marginals are Gaussian. In a number of studies, Mutual Information (MI) has been employed, as a similarity measure between each two time series of the brain regions, a pure nonlinear measure. Owing to the complex fractal organization of the brain indicating self-similarity, more information on the brain can be revealed by fMRI Fractal Dimension (FD) analysis. Methods: In the present paper, Box-Counting Fractal Dimension (BCFD) is introduced for graph theoretical analysis of fMRI data in 17 methamphetamine drug users and 18 normal controls. Then, BCFD performance was evaluated compared to those of LC and MI methods. Moreover, the global topological graph properties of the brain networks inclusive of global efficiency, clustering coefficient and characteristic path length in addict subjects were investigated too. Results: Compared to normal subjects by using statistical tests (P

PILs are promising solvent systems for CO2 absorption and transformations. Although previously tremendous work has been paid to synthesize functionalized PILs to achieve a high-performance absorption, the underlying mechanisms are far less investigated and still not clear. In this work, a series of DBU-based PILs, i.e., [DBUH][X], with anions of various basicities were synthesized. The basicities of the anions were accurately measured in [DBUH][OTf] or extrapolated from the known linear correlations. The apparent kinetics as well as the capacities for CO2 absorption in these PILs were studied systematically. The results show that the absorption rate and capacity in [DBUH][X] are in proportional to the basicity of PIL, i.e., a more basic PIL leads to a faster absorption rate and a higher absorption capacity. In addition, the spectroscopic evidences and correlation analysis indicate that the capacity and mechanism of CO2 absorption in [DBUH][X] are essentially dictated by the basicities of anions of these PILs.

The average monthly temperature of the lower troposphere (TLT) retrieved from satellite sensing data for 1979–2017 in the Southern Urals is analyzed. The method of decomposition of the temperature series into empirical orthogonal components (EOCs) was used to study the spatiotemporal TLT structure. Correlation analysis of the identified EOCs for winter and summer seasons and the indices of large-scale modes of natural climatic variability in the Northern Hemisphere is carried out. The first leading EOC, which characterizes a negative temperature trend, produces the main contribution to the overall variability. In winter, the leading mode is associated with the North Atlantic oscillation. In summer, a significant contribution of the Atlantic multidecadal oscillation and the index of the Arctic sea ice concentration anomalies was revealed. This may be used to improve the reliability of forecasting the regional climate change in the coming decades. The results suggest that the natural climatic variability has a considerable effect on the temperature regime and that it might be difficult to isolate the anthropogenic component of climate change in the studied region. [ABSTRACT FROM AUTHOR]

The α-H acidity is an important chemical property of ketones that has attracted much research interest. Theoretical prediction of pKa for ketone α-H is significant. In this work, we theoretically studied the nuclear shielding of various α-Hs in a set of ketones and that of the corresponding enolic hydroxyl Hs in tautomeric enol forms. It has been demonstrated through linear regression analyses that the pKa values of these ketones correlate with both sets of the calculated nuclear shielding values. The correlation coefficient R2 of the linear correlation relationship is 0.90. The present work has provided a new approach to computationally evaluating the acidity of α-Hs in ketones, enabling us to semi-empirically predict the ketone α-H acidity from the calculated nuclear shielding values. [ABSTRACT FROM AUTHOR]

The laminar burning velocity of nine different syngas compositions has been measured at elevated temperatures (350–650 K) for various equivalence ratios using an externally heated diverging channel method. The measured values are compared with the predictions of two detailed kinetic models (GRI 3.0 and FFCM-1). The predictions of FFCM-1 for various syngas (H 2 /CO/CH 4 /CO 2 /N 2) mixtures accurately capture the fundamental combustion characteristics, and GRI 3.0 mechanism overpredicts the laminar burning velocity for fuel rich syngas compositions. Temperature exponents mildly decrease with increase in equivalence ratio for mixtures investigated in the present work. Two correlations, one using linear regression, and another, a linear equation model is proposed to predict the laminar burning velocity accurately for various syngas compositional modifications. The developed linear model can be used for direct calculation of laminar burning velocities of different syngas compositions. Similarly, a temperature exponent correlation and its comparison with present measurements and simulations are also presented. The efficacy of the proposed models is evaluated through a detailed comparison with the literature. The model provides an excellent matching for following syngas compositions; 0.05 < X H 2 < 0.50 , 0.08 < X CO < 0.50, 0 < X C H 4 < 0.13, 0 < X C O 2 < 0.50, 0 < X N 2 < 0.65, for an equivalence ratio of ϕ = 0.7–1.25, and mixture temperature from 300 to 650 K. • Burning velocities of 9 different compositions of syngas were measured at elevated temperatures. • Quick approximation of laminar burning velocity of syngas-air mixtures. • Two correlations based on the experimental measurements are proposed. • Prediction by the proposed models is accurate for the compositional variability of syngas mixtures (H 2 / CO/ CH 4 / CO 2 / N 2). [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Increase of 50% in the Q C O 2 reduced in 33.3% the extraction dynamic period. • Lutein and antioxidant capacity was found in both extracts. • Extract was antihypercholesterolemic, antiatherosclerogenic, and antithrombogenic. • CO 2 +EtOH-SFE of defatted dried pulp was selective for phenolic compounds. • Linear correlation phenolic compounds×antioxidant capacity was positive. Abstract The obtaining of muruci extracts (Byrsonima crassifolia) was performed by CO 2 -SFE and CO 2 +EtOH-SFE, which were conducted at 323.15 K–343.15 K, and at 15 MPa to 49 MPa. The increase of 50% in the solvent flow rates, and the reduction of 33% in the dynamic period increased the yields. For the CO 2 -SFE, the highest values of global yield (9.12%), lutein (207.18 μg/g), and antioxidants (33.91 μmol TE/g) were obtained at 333.15 K. In the CO 2 +EtOH-SFE of the defatted freeze dried murici pulp, the highest values of lutein (209.73 μg/g), phenolics (43.69 mg GAE/g), and antioxidants (138.85 μmol TE/g) were obtained at 940 kg/m3, with a strong positive phenolics/antioxidants correlation. The functional quality suggests hypercholesterolemic, antiatherosclerosis and antithrombogenic effects. [ABSTRACT FROM AUTHOR]