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BACKGROUND: Myopia is a frequent visual problem, and the relationship between choroidal thickness (CT) and the degree of myopia has been a hot topic in myopia research. OBJECTIVE: This work aimed to explore the correlation between CT and the degree of myopia, providing a reference for diagnosing and treating myopia. METHODS: A cross-sectional study was conducted from September 2021 to December 2022, collecting data from 95 myopic patients aged between 18 and 50 years in the outpatient department. All subjects' CT in the macular center (MC), spherical equivalent (SE), and other ocular parameters were measured. Furthermore, the Pearson correlation coefficient (PCC) analyzed relationships between CT and various factors. RESULTS: The choroid was thickest in the MC and gradually became thinner towards the periphery, with the thinnest region located nasally in the healthy group. In the mild, moderate, and severe myopia groups, the choroid was thickest at 1,000 μ m temporal to the fovea, becoming thinner towards the periphery, with the thinnest region located nasally. The MC's CT was correlated with a family history of myopia, SE, axial length (AL), and intraocular pressure (IOP). Meanwhile, there was a negative linear relationship between AL and CT in the MC (standard coefficient (SC) of - 0.596, P -value of 0.000, tolerance of 0.217, and variance inflation factor (VIF) of 4.467), and a positive linear correlation between SE and CT in the MC (SC of 0.205, P -value of 0.013, tolerance of 0.257, and VIF of 3.792). CONCLUSION: This work provided clues for further understanding of the pathogenesis of myopic eyes and served as a scientific basis for early screening and treatment of myopia. Additionally, investigating the correlation between myopia and CT can also yield a reference for developing personalized myopia management strategies, which will help slow down myopia's progression and prevent related complications. [ABSTRACT FROM AUTHOR]

The inter-decadal variability of the Indian Summer Monsoon Rainfall (ISMR) has been conventionally considered to be an important indicator of climate change. This variability can be studied in terms of the significant periodicities underlying the rainfall time series. The present endeavour implements the Welch technique to estimate the Power Spectral Density (PSD) of rainfall data of the period of 1901–2005 to identify the significant periodicities at all India and at gridded scale. The analysis reveals that the sub-decadal periodicities in the ranges of (2, 3), (3, 5) and (5, 10) years have prevailed over 54%, 30% and 26%, respectively, of the subcontinental stretch individually, and about 82% of the total land area by combined action over the last century. Driven by the need to determine the interplay of these dominant sub-decadal periodicities in causing extreme rainfall occurrences this work seeks to correlate their interference patterns with the recorded rainfall amount. The results show the presence of a linear relationship within the range (0.5, 1) across diverse combinations of sub-decadal periodicities. [ABSTRACT FROM AUTHOR]

Steric manipulation is a known concept in molecular recognition but there is currently no linear free energy relationship correlating sterics to the stability of receptor‐anion complexes nor to the reactivity of the bound anion. By analogy to Tolman cone angles in cation coordination chemistry, we explore how to define and correlate cone angles of organo‐trifluoroborates (R−BF3−) to the affinities observed for cyanostar‐anion binding. We extend the analogy to a rare investigation of the anion's reactivity and how it changes upon binding. The substituent on the anion is used to define the cone angle, θ. A series of 10 anions were studied including versions with ethynyl, ethylene, and ethyl substituents to tune steric bulk across the sp, sp2 and sp3 hybridized α‐carbons bearing 0, 1 and 2 hydrogen atoms. A linear relationship between affinity and cone angle is observed for anions bearing substituents larger than the −BF3− headgroup. This correlation predicted affinities of two new anions to within ±5 %. We explored how complexation affects the reactivity of fluoride exchange. The yield of fluoride transfer from R−BF3− to Lewis acid triphenylborane is correlated with cone angle. We predict that other rigid macrocycles, like commercially available bambusuril, could follow these trends. [ABSTRACT FROM AUTHOR]

The objective of this article is to investigate the dependencies between selected European subindices before and during the COVID-19 pandemic. Research Design & Methods: The main analysis was quantitative. We used copula entropy and Pearson’s correlation. We considered the closing prices of sectoral indices from France (CAC sectors), Germany (DAX sectors), the UK (FTSE sectors), and the US (SP sectors), along with the main indices from these countries, that is CAC40, DAX, SP500, and FTSE100 (we collected the data from the database investing.com for the period from 4 January 2017 to 30 March 2023). We performed all analyses using R along with supplementary packages. Findings: When it comes to indications of the strength of dependence before and after the event (the outbreak of the COVID-19 pandemic) in relation to mutual information (delta) and linear correlation, we saw the biggest differences for the German market. For the DAX sectors, linear correlation underestimates post-event dependencies. The dependencies for other countries were similar on average. For half of the sectors (all markets), we recorded an increase in dependence after the event. A sector where we recorded growth in all countries was the TECH sector. Implications & Recommendations: The dependence measurement using mutual information expressed in terms of copulas has many advantages. It is not limited to measuring linear correlations. It can also capture a nonlinear correlation. Furthermore, it not only measures the dependence degree, but also considers the dependence structure, which is more than a correlation. Moreover, there was no assumption about the ellipticity of marginal and joint distribution. This dependence measure even allows for the modelling of the dependence of variables with different cumulative distribution functions. Contribution & Value Added: The novelty of this article is that it compares the results of dependence measurements by linear correlations and mutual information expressed in terms of copula entropy. Considering the indices and subindices of the main European stock markets, when both measures of dependence were used, we obtained significantly different results in both subperiods under investigation (i.e. before and after March 11, 2020). [ABSTRACT FROM AUTHOR]

In adults with type 1 diabetes (T1D), time in range (TIR) [70–180 mg/dL] has been proposed as an additional metric besides glycated hemoglobin (HbA1c). This retrospective monocentric cohort study determined the correlation between HbA1c and TIR during the 2, 4, and 12 weeks (TIR2w, TIR4w, and TIR12w) before consultation in a pediatric T1D population. A total of 168 children with T1D were included. Continuous glucose monitoring data, HbA1c, and demographic variables were collected. We found strong linear correlations between HbA1c and TIR2w (R = −0.571), HbA1c and TIR4w (R = −0.603), and between HbA1c and TIR12w (R = −0.624). A strong correlation exists between TIR2w and TIR12w, HbA1c and time above range (TAR), and between TIR and TAR at different time points. In conclusion, a strong correlation was found between HbA1c and TIR, making TIR a potentially complementary metric to HbA1c. TIR2w seems a viable alternative to TIR12w. TAR also seems promising in assessing glycemic control. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the gradient properties of bamboo at the microscopic level and provide a basis for improving the utilization rate of bamboo. Using moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) as a research subject, the variation of vascular bundle area percentage, chemical content, relative crystallinity (CR), mechanical properties of different bamboo slivers, and correlation between those parameters were analyzed. From the bamboo green layer (BGL) to the bamboo yellow layer (BYL), the distribution of vascular bundles changed from dense to sparse. Cellulose and lignin mass content decreased gently, and hemicellulose mass content showed gradual increases. The CR showed an order of bamboo middle layer (BML) > BGL > BYL. The tensile modulus of elasticity, tensile strength, bending modulus of elasticity, and bending strength decreased from BGL to BYL. The order of influence degree on mechanical properties of moso bamboo was vascular bundle area, hemicellulose content, lignin mass content, density, and CR, and these factors correlated with mechanical properties at a significant level (p < 0.05). Vascular bundle area had a decisive effect on the mechanical properties of bamboo. The vascular bundle area and density were linearly correlated with mechanical properties, while the lignin mass content and CR were curve-linearly correlated with mechanical properties. [ABSTRACT FROM AUTHOR]

Migraine and severe headaches are extremely prevalent neurological disorders that plague humans and society. Prior research has revealed that DII may affect the occurrence of migraines, but there are too few relevant studies and more are required. This study aimed to determine the association between severe headache or migraine and the Dietary Inflammatory Index (DII), with particular attention to age and gender differences. Using data from the National Health and Nutrition Examination Survey (NHANES), we performed a cross-sectional study. In addition, we investigated the association between DII and severe headache or migraine using weighted multivariate logistic regression models, and restricted cubic splines models were plotted to explore their linear correlation. There were a total of 13,439 people participating in the study, and of those, 2745 experienced a severe headache or migraine within the previous three months. The DII was linearly and positively correlated with severe headache or migraine (odds ratio [OR] = 1.05, 95% confidence interval [CI] = 1.01–1.08, p = 0.0051). Stratified analysis showed that this relationship persisted among women and those aged < 60 years, with ORs of 1.08 (95% CI = 1.04–1.13, p = 0.0004) and 1.05 (95% CI = 1.01–1.09, p = 0.0071), respectively. We found that greater levels of DII were significantly related to an increased likelihood of migraine onset, especially among women and young and middle-aged populations. Further research is required to validate and expand upon our results. [ABSTRACT FROM AUTHOR]

The article presents the worldwide harmonized light-duty test cycle results of a diesel engine passenger vehicle carried out on a chassis dynamometer. Pollutant emissions from exhaust and fuel consumption were measured. Vehicle velocity was treated as a variable determining pollutant emissions and fuel consumption because the engine operating states depend on engine velocity and load during engine operation, and these states in turn affect pollutant emissions and fuel consumption. Actions taken to reduce pollutant emissions and consumption of fuel are often in opposition to each other. Therefore, there is a need to optimize these activities. There is also a need to know the relationship between the effects of taking specific actions that serve to achieve individual goals in order to rationalize actions aimed at reducing pollutant emissions and fuel use. The originality of the article lies in the use of the correlation theory between pollutant emission and fuel consumption as well as the processes that determine them, primarily vehicle velocity, to rationalize these activities. Pearson's linear correlation theory was used to assess the relationships between individual variables. Significant differences were found in the correlation coefficients between individual variables, which confirmed the need to take integrated actions to reduce pollutant emissions and fuel consumption. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology 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.)

Linear correlated fuzzy differential equations (LCFDEs) are a valuable approach to handling physical problems, optimizations problems, linear programming problems etc. with uncertainty. But, LCFDEs employed on spaces with symmetric basic fuzzy numbers often exhibit multiple solutions due to the extension process. This abundance of solutions poses challenges in the existing literature's solution methods for LCFDEs. These limitations have led to reduced applicability of LCFDEs in dealing with such types of problems. Therefore, in the current study, we focus on establishing existence and uniqueness results for LCFDEs. Moreover, we will discuss solutions in the canonical form of LCFDEs in the space of symmetric basic fuzzy number which is currently absent in the literature. To enhance the practicality of our work, we provide examples and plots to illustrate our findings.

For the preparation of phenolic extracts, heating is one of the treatments applied. The efect of this type of heat treatment on the phenolic composition and the antioxidant power of olive leaves extracts were studied. This study aims to assess the use of solar heating method, a revolutionary green technology for the efcient extraction of several phytochemicals from food by-products. Olive leaves (Olea europaea L.) were used as the source material for this study. Solar heating method has been used for the extraction of polyphenols and favonoids compounds. The extracts of solar heating method, decoction, and maceration were characterized in terms of total phenolic compounds, total favonoids compounds, and their antioxidant activity based on 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity. The results showed that solar heating method extract provided a very satisfactory extraction yield in polyphenols, favonoids compounds, and antioxidants (189.58 mg GAE/g DW, 87.53 mg QE/g DW, and 91.16% respectively), which was higher than that attained by decoction and maceration methods. Moreover, HPLC analyses showed an increase in rutin, oleuropein, hydroxytyrosol, vanillin, coumaric acid, quercetin, and cafeic acid levels in the solar heating method extract. Results indicated solar heating method as a good choice for green recovering polyphenols and antioxidants from the olive leaves. There was a positive linear correlation between antioxidants, polyphenols, and between antioxidants, favonoids for solar heating method extract (coefcient r=0.89 and 0.77, respectively). These results suggested that the polyphenols and favonoids contributed significantly to the antioxidants of the investigated olive leaves. [ABSTRACT FROM AUTHOR]

In recent decades, an important number of regional and global digital elevation models (DEMs) have been released publicly. As a consequence, researchers need to choose between several of these models to perform their studies and to use these DEMs as third-party data to compute derived products (e.g., for orthorectification). However, the comparison of DEMs is not trivial. For most quantitative comparisons, DEMs need to be expressed in the same coordinate reference system (CRS) and sampled over the same grid (i.e., be at the same ground sampling distance with the same pixel-is-area or pixel-is-point convention) with heights relative to the same vertical reference system (VRS). Thankfully, many open tools allow us to perform these transformations precisely and easily. Despite these rigorous transformations, local or global planimetric displacements may still be observed from one DEM to another. These displacements or disparities may lead to significant biases in comparisons of DEM elevations or derived products such as slope, aspect, or curvature. Therefore, before any comparison, the control of DEM planimetric accuracy is certainly a very important task to perform. This paper presents the disparity analysis method enhanced to achieve a sub-pixel accuracy by interpolating the linear regression coefficients computed within an exploration window. This new method is significantly faster than oversampling the input data because it uses the correlation coefficients that have already been computed in the disparity analysis. To demonstrate the robustness of this algorithm, artificial displacements have been introduced through bicubic interpolation in an 11 × 11 grid with a 0.1-pixel step in both directionsThis validation method has been applied in four approximately 10 km × 10 km DEMIX tiles showing different roughness (height distribution). Globally, this new sub-pixel accuracy method is robust. Artificial displacements have been retrieved with typical errors (eb) ranging from 12 to 20% of the pixel size (with the worst case in Croatia). These errors in displacement retrievals are not equally distributed in the 11 × 11 grid, and the overall error Eb depends on the roughness encountered in the different tiles. The second aim of this paper is to assess the impact of the bicubic parameter (slope of the weight function at a distance d = 1 of the interpolated point) on the accuracy of the displacement retrieval. By considering Eb as a quality indicator, tests have been performed in the four DEMIX tiles, making the bicubic parameter vary between −1.5 and 0.0 by a step of 0.1. For each DEMIX tile, the best bicubic (BBC) parameter b* is interpolated from the four Eb minimal values. This BBC parameter b* is low for flat areas (around −0.95) and higher in mountainous areas (around −0.75). The roughness indicator is the standard deviation of the slope norms computed from all the pixels of a tile. A logarithmic regression analysis performed between the roughness indicator and the BBC parameter b* computed in 67 DEMIX tiles shows a high correlation (r = 0.717). The logarithmic regression formula b ~ σ s l o p e estimating the BBC parameter from the roughness indicator is generic and may be applied to estimate the displacements between two different DEMs. This formula may also be used to set up a future Adaptative Best BiCubic (ABBC) that will estimate the local roughness in a sliding window to compute a local BBC b ~ . [ABSTRACT FROM AUTHOR]

Tap water is a primary source for drinking water and other human activities in villages. The Bureau of Indian Standards (BIS) measures the quality of drinking water. The water samples used for drinking purposes from twenty-one villages of Malwa Punjab, India, were collected and analyzed from January 2022 to June 2022. To determine water quality, physicochemical parameters such as color, odor, pH, temperature, EC, TDS, TH, alkalinity, and the presence of ions (Cl−, SO42−, NO3−, F−, Na+, K+, Ca2+) were tested. The results of collected tap water samples were compared with standards of drinking water issued by WHO and the Government of India. It is found that some of the samples are not fit for drinking purposes. In the present study, statistical methods — linear correlation and regression analysis of water samples of these villages of the Malwa belt — are carried out to correlate the data of various parameters, using correlation coefficients and regression equations. Based upon this analysis, the quality of water in the villages can be easily determined at different points keeping the same source. A Piper diagram is also plotted to understand and compare the ionic composition present in given water samples. [ABSTRACT FROM AUTHOR]

Efficient and affordable batteries require the design of novel organic electrode materials to overcome the drawbacks of the traditionally used inorganic materials, and the computational screening of potential candidates is a very efficient way to identify prospective solutions and minimize experimental testing. Here we present a DFT high‐throughput computational screening where 86 million molecules contained in the PUBCHEM database have been analyzed and classified according to their estimated electrochemical features. The 5445 top‐performing candidates were identified, and among them, 2306 are expected to have a one‐electron reduction potential higher than 4 V versus (Li/Li+). Analogously, one‐electron energy densities higher than 800 Whkg−1 have been predicted for 626 molecules. Explicit calculations performed for certain materials show that at least 69 candidates with a two‐electron energy density higher than 1300 Whkg−1. Successful molecules were sorted into several families, some of them already commonly used electrode materials, and others still experimentally untested. Most of them are small systems containing conjugated CO, NN, or NC functional groups. Our selected molecules form a valuable starting point for experimentalists exploring new materials for organic electrodes. [ABSTRACT FROM AUTHOR]

Linear correlated fuzzy differential equations (LCFDEs) are a valuable approach to handling physical problems, optimizations problems, linear programming problems etc. with uncertainty. But, LCFDEs employed on spaces with symmetric basic fuzzy numbers often exhibit multiple solutions due to the extension process. This abundance of solutions poses challenges in the existing literature's solution methods for LCFDEs. These limitations have led to reduced applicability of LCFDEs in dealing with such types of problems. Therefore, in the current study, we focus on establishing existence and uniqueness results for LCFDEs. Moreover, we will discuss solutions in the canonical form of LCFDEs in the space of symmetric basic fuzzy number which is currently absent in the literature. To enhance the practicality of our work, we provide examples and plots to illustrate our findings. [ABSTRACT FROM AUTHOR]

Objective: The objective of this article is to investigate the dependencies between selected European subindices before and during the COVID-19 pandemic. Research Design & Methods: The main analysis was quantitative. We used copula entropy and Pearson’s correlation. We considered the closing prices of sectoral indices from France (CAC sectors), Germany (DAX sectors), the UK (FTSE sectors), and the US (SP sectors), along with the main indices from these countries, that is CAC40, DAX, SP500, and FTSE100 (we collected the data from the database investing.com for the period from 4 January 2017 to 30 March 2023). We performed all analyses using R along with supplementary packages. Findings: When it comes to indications of the strength of dependence before and after the event (the outbreak of the COVID-19 pandemic) in relation to mutual information (delta) and linear correlation, we saw the biggest differences for the German market. For the DAX sectors, linear correlation underestimates post-event dependencies. The dependencies for other countries were similar on average. For half of the sectors (all markets), we recorded an increase in dependence after the event. A sector where we recorded growth in all countries was the TECH sector. Implications & Recommendations: The dependence measurement using mutual information expressed in terms of copulas has many advantages. It is not limited to measuring linear correlations. It can also capture a nonlinear correlation. Furthermore, it not only measures the dependence degree, but also considers the dependence structure, which is more than a correlation. Moreover, there was no assumption about the ellipticity of marginal and joint distribution. This dependence measure even allows for the modelling of the dependence of variables with different cumulative distribution functions. Contribution & Value Added: The novelty of this article is that it compares the results of dependence measurements by linear correlations and mutual information expressed in terms of copula entropy. Considering the indices and subindices of the main European stock markets, when both measures of dependence were used, we obtained significantly different results in both subperiods under investigation (i.e. before and after March 11, 2020).

IntroductionThe temperature of the earth has been rising by about 0.74 degrees Celsius over the past century. A gradual increase in the average annual temperature has been reported by many researchers worldwide, while other reports suggest a decrease in this parameter. The assumption is that there will be more areas of the world experiencing higher temperatures. The climate changes are effectively represented by temperature changes, which is considered one of the main indicators in climate studies. The chemical composition of the atmosphere has changed because of the increase in human industrial activities, so it is responsible for unprecedented changes in the global climate in the past century. The increase in greenhouse gas concentration is the cause of this change. The evidence indicates that the increase in atmospheric gas concentration has caused a significant increase in global temperature. The use of thermal data from sensors is widely used in the study of terrestrial phenomena, as indicated by many studies. The temperature of the earth's surface is directly and indirectly linked to all human activities. It is still not possible to calculate the temperature of the earth's surface with perfect and accurate methods, but some sensors with suitable temporal, spectral, and spatial performance are able to take photos of the entire surface of the Earth. The study is more important due to the fact that various species of animals, such as Jebeer (belonging to the Bovidae), are exposed to climate changes in arid and desert areas. Due to its impact on humans, other creatures, and the entire environment, it is imperative to pay attention to climate change nowadays. In this regard, the main aim of the current study is to evaluate the LST (Land Surface Temperature) trends, changes, and temperature threats of the land surface in the Central Plateau of Iran. Time series remote sensing data of the MODIS (MOD11A2) sensor and Terra satellite, in 8 days with spatial resolution of 1km from 2002 to 2018 have been used. Material and Methods The current study has been focused on the central plateau of Iran. The central plateau of Iran lies within the arid lands belt of the northern hemisphere. The current study has been attempting to extract exact information from the images by employing specific techniques. To achieve this goal, the MOD11A2 product of Terra satellite MODIS sensor, the trend of temperature changes and time series construction of the significance of Man Kendall methods and linear correlation parameters such as maximum monthly temperature, maximum annually temperature based on maximum monthly temperature, median monthly temperature, maximum annually temperature based on median monthly temperature, minimum monthly temperature, minimum annually temperature for daily and nightly temperature were used in TerrSet software and Earth Trends Modeler section to extract significant increasing and decreasing areas. After identifying some parts of provinces with significant temperatures based on analysis and results, we can identify the vital numerical value of the temperature in each pixel of those significant parts in the next stage. This can be achieved by utilizing the difference between the final temperature and the initial temperature. Trend analysis was used to simulate daily and nightly temperature changes for parameters of maximum monthly temperature, maximum annually temperature based on maximum monthly temperature, median monthly temperature, maximum annually temperature based on median monthly temperature, minimum monthly temperature and minimum annual temperature. Results and DiscussionDaily temperature data in the Central Plateau of Iran, which includes monthly minimum temperature, annual minimum temperature, monthly maximum temperature, annual maximum temperature based on monthly maximum temperature, monthly median temperature and annual maximum temperature based on monthly median temperature, common in Semnan and Isfahan provinces, showed a significant increase in linear correlation according to the results. In Isfahan province, the linear correlation decreased significantly between the maximum annual temperature based on the maximum monthly temperature and the median monthly temperature. There was no significant trend in other provinces. The linear correlation between temperature data in Isfahan and Semnan provinces, including the minimum monthly, minimum annual, maximum annual, and median monthly temperature, decreased significantly. The linear correlation between average annual temperature, average monthly temperature, maximum annual temperature determined by maximum monthly temperature, average monthly temperature, and maximum annual temperature determined by median monthly temperature increased significantly in Yazd and Isfahan provinces. No significant trends were observed in other provinces. To estimate the amount and approximate number of significant increases and decreases, simulations of temperature changes were conducted. The range and approximate range of numbers for significant increase and decrease in temperature were calculated in degrees Celsius. In all analyses, the parts with higher temperatures had a reddish color. The intensity of the red color increased as the temperature increased, and as the temperature decreased, the red color became fainter and turned blue. The central plateau of Iran recorded a maximum temperature of 44C°and a minimum temperature of -7C°according to this study. The central plateau of Iran has three main provinces, which include Isfahan, Semnan, and Yazd. Considering the temperatures mentioned for these three provinces, the temperatures obtained from this study are very similar, which means that the conducted study is approved to a large extent. Animals are considered to be at risk due to temperature changes. Future research should emphasize the impact of climate change and temperature increase on the living conditions of various animals, particularly those found on the central plateau of Iran.

This paper constructs a multiple regression analysis model of the agricultural industry chain with rural environment and economic management and estimates the model parameters using the least squares method. The linear correlation between the variables is analyzed based on the variance expansion coefficient, standardization coefficient, complex correlation coefficient and other indicators, and the regression problem is analyzed for significance. Then the antidifferential Kalman filter optimization method of least squares and the threshold denoising optimization method based on wavelet decomposition and reconstruction transformation are introduced to optimize the model parameters to improve the model performance. Finally, the impact of agricultural industry chain construction on the rural environment and economic management is analyzed based on the model. The correlation coefficients between the three dimensions of agricultural product industry chain management and the performance of rural economic management are 0.318, 0.468, 0.416, and the correlation coefficients between them and the performance of rural environmental management are 0.297, 0.528, and 0.529, respectively, which indicates that rural agricultural product industry chain construction can promote rural management.

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) 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.)

The objective of this study was to identify the linear relationships between the morphological variables of corn hybrids, associated with grain yield and fungicide use in subtropical environments. Seven experiments were conducted in three locations: Santa Maria - RS, São Vicente do Sul - RS, and Frederico Westphalen - RS, Brazil. The design used was a randomized block design with subdivided plots and three replications, where the main factor was the use or not of fungicide and the subplots corresponded to six corn hybrids. The following traits were evaluated: leaf angle, stem diameter, ear insertion height, ear length, ear diameter, number of rows, grain length, thousand-grain mass, percentage of damaged grains, and grain yield. The characters were subjected to Pearson correlation analysis and path analysis using R software. It can be concluded that there is a difference in the magnitudes of the linear relationships depending on whether or not fungicides are used on corn hybrids in subtropical environments, with cultural management influencing the results of the linear relationships. The characters ear diameter, grain length, ear length, and thousand-grain mass are positively related, while leaf angle and the percentage of damaged grains are negatively related to grain yield in corn hybrids. [ABSTRACT FROM AUTHOR]

Maps of lunar wrinkle ridges (LWRs) were created from 70°N to 70°S and 140°E to 140°W (extracted and highlighted the major LWRs area) using automated LWRs detection process with Lunar Reconnaissance Orbiter Camera wide range angle camera and Lunar Orbiter Laser Altimeter data. Automatic detection of LWRs is challenging because the ridges are of irregular shapes and many ridges have been eroded and/or degraded over time. It’s a preliminary study of automated ridge detection from DEM data. Statistics and measurements of the extracted LWRs, including orientation, extent, length, height, and elevation offset, were performed based on the mapping of lunar ridges. The identified ridges were classified based on their orientation, distribution, direction, and each class were further divided over basalts, and nearby highlands. According to the findings, 3,375 segments with a total length of 26,455.01 km were identified, and the average elevation offset, width, and height of all the wrinkle ridges were 40.39 m, 3.47 km, and 0.29 km respectively after weighting by length. The LWRs were divided into three morphologies and distributions: parallel ridges, isolated ridges, and concentric ridges. The vast majority of LWRs were found in basalts area, with an extension into neighboring highland. The relations between the morphological parameters were further quantitatively analyzed, and a similar linear correlation between the width and height was found in each class of lunar ridges, implying that small and large ridges were formed as a continuum and that the three classes of ridges were probably formed by some common processes. Finally, the relations between the lunar wrinkle ridges and other geomorphic phenomena were analyzed, indicating that purely volcanic origin or buried premare structures are difficult to reconcile with the investigation. In addition, the consistency between the occurrence of the lunar wrinkle ridges and the thickness of lunar maria indicates that the formation of lunar wrinkle ridges is closely related to the lunar maria; nevertheless, the statistical NW direction of individual classes of LWRs also proposes the presence of an appropriate stress field during the process of their formation.

A fast HPLC method was developed to study the hydrophobicity extent of pharmaceutically relevant molecular fragments. By this strategy, the reduced amount of sample available for physico‐chemical evaluations in early‐phase drug discovery programs does not represent a limiting factor. The sixteen acid fragments investigated were previously synthesized also determining potentiometrically their experimental log D values. For four fragments it was not possible to determine such property since their values were outside of the instrumental working range (2 < pKa < 12). An RP‐HPLC method was therefore optimized. For each scrutinized method, some derived chromatographic indices were calculated, and Pearson's correlation coefficient (r) allowed to select the so‐called "φ0 index" as the best correlating with the log D. The wspH${}_w^spH$ was fixed at 3.5 and a modification of some variables [organic modifier (methanol vs. ACN), stationary phase (octyl vs. octadecyl), presence/absence of the additives n‐octanol, n‐butylamine, and n‐octylamine], allowed to select the best correlation conditions, producing a r = 0.94 (p < 0.001). Importantly, the φ0 index enabled the estimation of log D values for four fragments which were unattainable by potentiometric titration. Moreover, a series of molecular descriptors were calculated to identify the chemical characteristics of the fragments explaining the obtained φ0. The number of hydrogen bond donors and the index of cohesive interaction correlated with the experimental data. [ABSTRACT FROM AUTHOR]

The efficient prediction of biomechanical properties of bone plays an important role in the assessment of bone quality. However, the present techniques are either of low accuracy or of high complexity for the clinical application. The present study aims to investigate the predictive ability of the evolving convolutional neural network (CNN) technique in predicting the effective compressive modulus of porous bone structures. The T11/T12/L1 segments of thirty-five female cadavers were scanned using the HR-pQCT scanner and the images obtained from it were used to generate 10896 2 D bone samples, in which only the cancellous bony parts were processed and investigated. The corresponding 10896 heterogeneous finite-element (FE) models were generated, and then a CNN model was constructed and trained using the predictions of the FE analysis as the ground truths. Then the remaining 260 bone samples generated from the initial HR-pQCT images were used to test the predictive power of the CNN model. The results show that the coefficient of the determinant (R2) from the linear correlation between the CNN and FE predicted elastic modulus is 0.95, which is much higher than that from the correlation between the BMD and the FE predictions (R2 = 0.65). Furthermore, the 95th and 50th percentiles of relative prediction error are below 0.28 and 0.09, respectively. In the conclusion, the CNN model can efficiently predict the effective compressive modulus of human cancellous bone and can be used as a promising and clinically applicable method to evaluate the mechanical quality of porous bone. [ABSTRACT FROM AUTHOR]

Despite the constant improvement of complex computer algorithms for the calculation of gas chromatographic retention indices (RIs), the simplest methods for their evaluation based on linear correlations between the indices of structural analogs from different taxonomic groups, RI1 ≈ aRI2 + b, remain important. It is shown that symbatic variations of the first numerical differences of retention indices, = RIn+ 1 – RIn (equivalent to the first derivatives of the retention indices with respect to the structural parameter varied in the group), are the conditions of correctness for such correlations in the simplest groups (substituted methanes). A monotonic variation of in one of the groups with the presence of extrema in the other group is an unequivocal sign of the absence of a linear correlation between retention indices. If the values of in one of the groups increase and decrease in the other, the ranking order of compounds in any one of them should be reversed. It is shown that the simplest relationship RI1 ≈ aRI2 + b is also applicable to more complex taxonomic groups (substituted ethanes, benzenes, and naphthalenes), and it allows one not only to estimate the RIs of compounds not yet characterized but also to refine known reference data. [ABSTRACT FROM AUTHOR]

Purpose: Investigating the correlation between the interlaminar space size on plain radiograph and lumbar spinal stenosis (LSS). Methods: 100 Patients with LSS and 100 normal participants without LSS were included in this study. Lumbar interlaminar parameters were measured on plain radiographs. Spinal canal parameters were measure on CT and MRI. These image parameters were compared between LSS and control group. The linear correlation among interlaminar parameters, spinal canal parameters and Oswestry Disability Index (ODI) were analyzed. The cut-off values of interlaminar parameters for diagnosing L3/4 and L4/5 symptomatic LSS were analyzed. Results: Excepting for L1/2 interlaminar width, all interlaminar and spinal canal related parameters in LSS group were significantly smaller than those in control group. Excepting for L1/2 interlaminar width and L5/S1 interlaminar height, all interlaminar parameters had significantly positive linear correlation with spinal canal parameters accordingly in each lumbar level. For diagnosis of symptomatic LSS, The cut off values of L4/5 interlaminar width, height and area were 18.46 mm, 11.37 mm and 134.05 mm2 while 15.78 mm, 13.59 mm and 157.98 mm2 in L3/4. Both spinal canal size and interlaminar size had no linear correlation with ODI in cases of L4/5 LSS. Conclusions: Lumbar interlaminar space size on plain radiograph has positive linear correlation with developmental and degenerative LSS, excepting for L1/2 interlaminar width and L5/S1 interlaminar height. Lumbar plain radiograph can be a feasible way for predicting and helping to diagnose LSS through evaluating the interlaminar space size. Level of Evidence: III [ABSTRACT FROM AUTHOR]

Copyright of Human Review is the property of Eagora Science 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.)

The research shows the results of using a model-eliciting activities for learning correlation and linear regression. With its resolution, the participants acquired, expanded, and refined their statistical knowledge and skills, organizing, analyzing, and representing data, establishing correlations, and determining regression lines and coefficients of determination. Also, with the proposed models, they concluded, explained, and described the phenomenon. In addition to establishing the activity as a pedagogical tool and a useful element for research in virtual environments, the study shows deficiencies in the modeling of students linked to planning prior to addressing the problem. [ABSTRACT FROM AUTHOR]

The objective of our research is to determine the impact of eating habits on anxiety. Eating habits were evaluated according to validated instruments and their normality was established with Kolmogorov-Smirnov K-S=0.9 and significance p-value= 0.3>0.05. We have that food consumption also has a normal distribution and does not impact the anxiety variable with a Pearson correlation of -0.08 and significance p-value=0.49. The logistic regression establishes the consumption cut-off point equal to 50 to have a 50% probability of having anxiety. Likewise, the punctual estimate of anxiety corresponding to this cut of consumption 50 is the score of 10. [ABSTRACT FROM AUTHOR]

Copyright of Revista Cientifica de la Facultade de Veterinaria is the property of Universidad del Zulia, Facultad de Ciencias Veterinarias 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.)

This study aimed to evaluate the influence of meteorological variables and geographic factors on the selection of soybean lines concerning grain yield in Brazil and Paraguay soybean-producing regions. The study was conducted in seven different environments: Bela Vista do Norte - PY, Palotina - PR, Mangueirinha - PR, Major Vieira - SC, Três Passos - RS, Toledo – PR, and Passo Fundo - RS. The randomized block design in an incomplete factorial scheme with six soybean genotypes (G1, G2, G3, G4, G5, and G6) was used for the experiments. The harvest occurred in the first half of March, and grain yield was measured through the total harvest of the plot and expressed in kg ha-1, with grain moisture at 13%. The climatic variables used in the study were maximum air temperature (Tmax, ºC), average air temperature (Tavg, ºC), minimum air temperature (Tmin, ºC), relative air humidity (RH, %), precipitation (Prec, mm), wind speed (WS, m/s), dew point (DP, °C), incident radiation (Rad_Inc, MJ/m²), and total radiation (RAD_OL, MJ/m²); and geographic factors were altitude (ALT), longitude (LON), and latitude (LAT). The G5 genotype with a genetic value for grain yield above the general average is the most adapted to favorable environments. Altitude had the greatest influence on the biological variability of the genotypes, with a negative correlation of moderate magnitude with grain yield. Grain yield was enhanced in environments with altitudes lower than 338 m at latitudes below 24.17S.

In recent decades, an important number of regional and global digital elevation models (DEMs) have been released publicly. As a consequence, researchers need to choose between several of these models to perform their studies and to use these DEMs as third-party data to compute derived products (e.g., for orthorectification). However, the comparison of DEMs is not trivial. For most quantitative comparisons, DEMs need to be expressed in the same coordinate reference system (CRS) and sampled over the same grid (i.e., be at the same ground sampling distance with the same pixel-is-area or pixel-is-point convention) with heights relative to the same vertical reference system (VRS). Thankfully, many open tools allow us to perform these transformations precisely and easily. Despite these rigorous transformations, local or global planimetric displacements may still be observed from one DEM to another. These displacements or disparities may lead to significant biases in comparisons of DEM elevations or derived products such as slope, aspect, or curvature. Therefore, before any comparison, the control of DEM planimetric accuracy is certainly a very important task to perform. This paper presents the disparity analysis method enhanced to achieve a sub-pixel accuracy by interpolating the linear regression coefficients computed within an exploration window. This new method is significantly faster than oversampling the input data because it uses the correlation coefficients that have already been computed in the disparity analysis. To demonstrate the robustness of this algorithm, artificial displacements have been introduced through bicubic interpolation in an 11 × 11 grid with a 0.1-pixel step in both directionsThis validation method has been applied in four approximately 10 km × 10 km DEMIX tiles showing different roughness (height distribution). Globally, this new sub-pixel accuracy method is robust. Artificial displacements have been retrieved with typical errors (eb) ranging from 12 to 20% of the pixel size (with the worst case in Croatia). These errors in displacement retrievals are not equally distributed in the 11 × 11 grid, and the overall error Eb depends on the roughness encountered in the different tiles. The second aim of this paper is to assess the impact of the bicubic parameter (slope of the weight function at a distance d = 1 of the interpolated point) on the accuracy of the displacement retrieval. By considering Eb as a quality indicator, tests have been performed in the four DEMIX tiles, making the bicubic parameter vary between −1.5 and 0.0 by a step of 0.1. For each DEMIX tile, the best bicubic (BBC) parameter b* is interpolated from the four Eb minimal values. This BBC parameter b* is low for flat areas (around −0.95) and higher in mountainous areas (around −0.75). The roughness indicator is the standard deviation of the slope norms computed from all the pixels of a tile. A logarithmic regression analysis performed between the roughness indicator and the BBC parameter b* computed in 67 DEMIX tiles shows a high correlation (r = 0.717). The logarithmic regression formula b~σslope estimating the BBC parameter from the roughness indicator is generic and may be applied to estimate the displacements between two different DEMs. This formula may also be used to set up a future Adaptative Best BiCubic (ABBC) that will estimate the local roughness in a sliding window to compute a local BBC b~.

We propose a signal- and sensitivity-enhanced spin-exchange-relaxation-free atomic magnetometer utilizing a multi-pass cell with a highly spatially homogeneous optical pumping scheme. The relationship between the magnetometer’s performance and the number of probe beam passes is measured. The optical rotation angle exhibits a linear correlation with the number of passes, achieving 89 mrad nT ^−1 for a quadruple-pass cell. However, the sensitivity does not increase linearly when further increasing the optical length due to the noise limit. This work provides a method to study the enhancement performance of the magnetic response and sensitivity in atomic magnetometers by using multi-pass cells.

The idealized urea electrocatalyst is crucial to boost the CN coupling reaction and simultaneously suppress their isolated reduction process after adsorbing N2 and CO2 molecules. Therefore, the dispersed MN3‐M′N4 moiety is investigated systematically, including 26 homonuclear and 650 heteronuclear di‐metal systems. After, 205 stable systems are selected using lowest‐energy principle and ab initio molecular dynamics simulations. According to three possible pathways, NCON, CO, and OCOH to produce urea, a five‐step high‐throughput screening method for excellent catalytic activity and a five‐aspect high‐throughput screening strategy for outstanding catalytic selectivity are proposed, respectively. The potential determined steps and the limiting potential through three pathways are identified. The data indicates both CO pathway and OCOH pathway are more competitive at lower Gibbs free energy. Significantly, the most favorite RuN3‐CoN4 combination possesses an extremely low limiting potential of −0.80 V for urea production, meanwhile it exists a strong foundation for experimental preparation. This work not only broadens electrocatalytic potentiality of developing di‐metals as two active sites, but also provides a feasible high‐throughput screening recipe for urea production. [ABSTRACT FROM AUTHOR]

Understanding the effect of grain size on the overall electrical and thermal transport properties of PRGO films on a large scale is not only fundamental but also technologically important in order to tune their properties for wide applications. In this work, by adjusting the annealing temperature, we control the density of the oxygen containing functional groups and thus the structural domain size of PRGO film. The annealing effect on the temperature dependency of thermal and electrical transport is studied. In addition, the linear relationship between thermal diffusivity and electrical conductivity is confirmed from 320 K to 10 K. The temperature dependent thermal diffusivity of the amorphous region in PRGO is reported. In the last, based on the residual thermal reffusivity at 0 K limit, the structure defects induced phonon mean free path against the annealing temperature is obtained, and compared with the cluster size calculated from XRD, TEM and Raman. A linear relationship among the structure domain size, thermal diffusivity, and electrical conductivity is further revealed, which demonstrates the strong effect of structure domain size on the thermal and electrical transport of PRGO. [Display omitted] • A linear relationship between the thermal diffusivity and electrical conductivity from 320 K to 10 K is reported in PRGO films with varying reduction level. The corresponding mathematical model is proposed. • The electrical transport is found to vary with the thermal reduction level, where the temperature coefficient of resistance (TCR) decreases as the annealing temperature increases, reflecting a tunable band gap. • Based on the residual thermal reffusivity at 0 K limit, the structure defects induced phonon mean free path against the annealing temperature is obtained, and compared with the cluster size calculated from XRD and Raman. • A linear relationship among the structure domain size, thermal diffusivity, and electrical conductivity is further revealed. [ABSTRACT FROM AUTHOR]

A new improved polyurethane materials was studied to improve the strength of paper, delay the aging of paper, solve the problem of poor permeability of traditional resins to paper, and meanwhile to provide basic data for industrial design and applications, the surface tension of composite solutions consisting of nano-SiO2-based polyurethane, organo siliconbased polyurethane and epoxy cyclohexane-epichlorohydrin polyurethane dissolved in ethyl acetate had been measured at temperatures ranging from 283.15 K to 308.15 K. The surface tension was fitted with the related equation between surface tension and temperature under normal pressure. The mean relative deviations between the calculated value and the experimental value were derived. The results showed that the model estimation of the surface tension of the composite solution were in good agreement with the experimental data, the paper coated by the polyurethane materials had better mechanical property. Therefore, the prepared polyurethane material has great application prospects in the protection of paper. [ABSTRACT FROM AUTHOR]

Objective: This study aims to assess the accuracy of linear alveolar bone measurements for implant planning using cone-beam computed tomography (CBCT) by comparing three 3D imaging software: CareStream (Carestream Health, Rochester, New York, United States), RadiAnt (Medixant, Poznan, Poland), and iRYS (Cefla s.c., Imola, Italy)., Methods: Twenty-seven dry goat mandibles were used for this in-vitro study. Gutta-percha markers were placed on the mandibles, which were then scanned using a CBCT machine. Linear measurements of the alveolar bone were taken at the implant sites using CareStream, RadiAnt, and iRYS software, and compared to gold-standard measurements obtained using digital Vernier calipers. Measurements included bone height and width, and the absolute measurement errors were calculated to assess accuracy., Results: iRYS consistently provided the most accurate measurements compared to the control, especially at lower error thresholds. RadiAnt tended to overestimate, while CareStream yielded intermediate values. Across all thresholds, iRYS showed the least deviation, followed by CareStream and RadiAnt. Statistical analysis showed no significant differences between the three software programs at higher error thresholds, confirming the reliability of each for implant planning., Conclusion: All three software programs (iRYS, CareStream, and RadiAnt) offered reliable and accurate measurements for implant planning using CBCT, with iRYS being the most accurate. Clinicians can confidently use any of the three, although iRYS may be preferred for cases requiring higher precision., Competing Interests: Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Animal subjects: Institutional Ethics Committee of Kalinga Institute of Medical Sciences Issued protocol number KIIT/KIMS/IEC/1291/2023. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Neralla et al.)

Gluten-free products are on today’s agenda since they represent the most hastily growing segments in the market, representing an opportunity for food companies. Nevertheless, it is well-known that gluten is a crucial network structure in the wheat dough systems, which accounts for the overall desired technological features of the final bakery goods. Therefore, the absence of gluten negatively affects the characteristics of gluten-free bread, triggering a technological challenge in the manufacturing of products with resembled characteristics of wheat-derived counterparts. The search for new protein sources has been studied as an approach to circumvent the technological drawbacks of gluten removal. Dairy proteins are functional molecules that can likely be capable of building up a protein-network structure so that it would improve the technological properties of gluten-free products. In the present work, different levels of dairy product addition (10 and 20%, w/w) were used to supplement the gluten-free bread formulas, and the impact on dough rheology properties was well correlated to the bread technological quality parameters obtained. Linear correlations (R2 > 0.904) between steady shear (viscosity) and oscillatory (elastic and viscous moduli) values of the dough rheology with bread quality parameters (volume and firmness) were obtained, suggesting that the bread quality improvements are proportional to the levels of dairies added. Likewise, strong linear correlations (R2 > −0.910) between pasting properties parameters and bread staling rate supported the hypothesis that the dairies tested have a high potential to generate bread with a low staling rate, which is an advantage to extending the shelf-life. In short, results confirmed that the addition of both dairy products, as bakery ingredients, can constitute a technological advantage to improve the overall gluten-free bread quality.

ObjectiveThis study aimed to investigate the correlation between component alignment and short-term clinical outcomes after total knee arthroplasty (TKA).Methods50 TKA patients from a regional hospital were enrolled in the study. The following component alignments were measured from radiological data acquired within 1 week after surgery: hip-knee-ankle angle (HKA), medial distal femoral angle (MDFA), medial proximal tibial angle (MPTA), femoral flexion-extension angle (FEA), tibial slope angle (TSA), femoral rotational angle (FRA) and tibial rotational angle (TRA). The Hospital for Special Surgery (HSS) knee scoring system was used to assess clinical outcomes after 1 year, with patients being divided into three groups (excellent, good and not good) according to the HSS scores. Difference analysis and linear correlation analysis were used for the statistical analysis.ResultsThe results showed significant differences in MDFA (p = 0.050) and FEA (p = 0.001) among the three patient groups. It was also found that the total HSS had only a moderate correlation with FEA (r = 0.572, p

The spatial distribution of soil pH, electrical conductivity, available nitrogen, phosphorus and potassium concentrations at Anaimalai block of Coimbatore district, India was interpolated by geostatistical analysis to create digital maps of soil NPK that renders numerous information for agro based policy making. 1627 soil samples in 30,700 acres were gathered by composite soil sampling method and rendered interpolation analysis to predict the soil parameters at unsampled locations. Based on geostatistical, deterministic and interpolation with barriers methods 13 interpolation models were generated and compared to validate the precision. Interpolation reveals the deficiency of soil available nitrogen and phosphorus whereas available potassium was in sufficient range. Radial basis function, inverse distance weighting, probability kriging, empirical Bayesian kriging and local polynomial interpolations were validated by linear correlation method that reveals the precisions of models with R2 values of 0.74, 0.82, 0.98, 0.89 and 0.79 (soil pH, EC, nitrogen, phosphorus and potassium respectively). [ABSTRACT FROM AUTHOR]

• A distributed detection method for surface strain of large diameter pipelines is proposed. • The PCCP (Prestressed Concrete Cylinder Pipe) circumferential surface strain profile evolution over time with respect to changing internal pressure is investigated and revealed continuously. • The feature of spatial strain distribution and its variation is analyzed in regard to pressure variation in different phases by distributed optical fiber sensing technique based on Brillouin optical time domain analysis (BOTDA). • The test results demonstrate that BOTDA sensing system is very reliable in the condition detection of large diameter long distance water pipeline. Prestressed concrete cylinder pipes (PCCPs) are widely used in trans -regional large-scale water conveyance projects, so it is of great significance to monitor their condition. In this paper, the Brillouin Optical time domain analysis (BOTDA) sensing system is used to measure the circumferential strain of PCCPs under internal water pressure. The test results show that BOTDA technology can accurately monitor the shape variable of the outer wall of the pipe. Moreover, the circumferential strain is not uniform, and there are multiple relative maxima and minima. When the internal water pressure is 1.2 MPa, the absolute maximum and minimum strain is 579.17με and 217.78με respectively. In addition, there is a positive linear correlation between the strain and the internal water pressure, but the hysteresis effect is obvious in the case of insufficient water filling. This study provides reliable experimental data for the application of distributed optical fiber sensing technology in large-diameter water pipelines. [ABSTRACT FROM AUTHOR]

Label distribution learning represents the relevance of labels to samples using description degree, which can provide richer semantic information, thus finding wider applications. Exploiting label correlations is an effective approach to narrow down the hypothesis space of label distribution learning models. In existing works that utilize low-rank assumptions or label linear dependence to mine correlations, it is assumed that a label can be linearly expressed by other labels. However, this assumption can only be satisfied when there are linear dependency relationships between labels, thus the label correlation obtained by such methods is subject to certain distortion. To address this issue, this paper assumes that labels can be linearly represented by the same set of bases. The correlation between labels is represented by sharing common bases. Specifically, the paper employs matrix factorization to extract bases that can be used to represent all labels. And then designs a label distribution learning algorithm based on the property of sharing the same set of bases of the ground truth label distribution and predict label distribution. The effectiveness of the algorithm is verified through experimental validation. Generally speaking, the algorithm presented in this paper achieves optimal performance at 73.15% of the cases, with the best average ranking. In the two-tailed t -test, the algorithm in this paper exhibits statistical superiority compared to all comparison algorithms. [ABSTRACT FROM AUTHOR]