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Indirect selection for yield in sugarcane (Saccharum officinarum L.) production can be achieved by identifying and selecting for plant traits that are correlated to yield. This study aimed to identify and quantify sugarcane traits that are associated with ratooning ability to generate information for varieties' selection. Data sourced from three variety trials established at three sites, comprising eight varieties, and collected over six successive crops (plant cane and five ratoons) were used for this study. The data were subjected to linear mixed model, Spearman's correlation, and biplot analyses. Stalk height, stalk population, stalk mass, and stalk sucrose mass were significantly correlated with cane and sucrose yield across all ratoon crops, suggesting that varieties that combine these traits over multiple crops will have higher ratoon cane and sucrose yields. Significant correlation between brix and sucrose content suggested that brix can be used to indirectly select for sucrose content. Measuring brix is easier, cheaper, and faster than measuring sucrose content. Significant site and variety effects on ratoon crop yields indicated the existence of opportunities to identify good ratooning varieties that are specifically and or broadly adapted to different growing conditions. [ABSTRACT FROM AUTHOR]

Classical supervised methods like linear regression and decision trees are not completely adapted for identifying impacting factors on a response variable corresponding to zero‐inflated proportion data (ZIPD) that are dependent, continuous and bounded. In this article we propose a within‐block permutation‐based methodology to identify factors (discrete or continuous) that are significantly correlated with ZIPD, we propose a performance indicator quantifying the percentage of correlation explained by the subset of significant factors, and we show how to predict the ranks of the response variables conditionally on the observation of these factors. The methodology is illustrated on simulated data and on two real data sets dealing with epidemiology. In the first data set, ZIPD correspond to probabilities of transmission of Influenza between horses. In the second data set, ZIPD correspond to probabilities that geographic entities (eg, states and countries) have the same COVID‐19 mortality dynamics. [ABSTRACT FROM AUTHOR]

This research aims to analyze the relationship between food packaging knowledge among meatball and chicken noodle sellers in Pondok Kelapa, Duren Sawit, East Jakarta, and their behavior regarding the use of plastic for hot food. The study was conducted from March 2022 to July 2023 in Pondok Kelapa, Duren Sawit, East Jakarta. Samples were taken from meatball and chicken noodle vendors operating in the area. Data was collected through a questionnaire consisting of 17 questions on knowledge variables and 18 statements on behavior variables. Non-parametric statistical methods, specifically the chi-square test and Spearman's correlation, were used for data analysis as an alternative to parametric methods when certain assumptions were not met. The results of the chi-square test indicated a value of 0.123, which is greater than 0.05. This suggests that there is no significant relationship between knowledge about food packaging and the behavior of using plastic for hot food. Meanwhile, the Spearman's correlation coefficient was calculated as 0.154, indicating a very weak relationship between food packaging knowledge and plastic usage behavior for hot food. The study, conducted with 39 respondents, showed that 49% had sufficient knowledge about food packaging, and 77% had adequate behavior in using plastic for hot food. It is hoped that meatball and chicken noodle sellers can improve their knowledge regarding plastic packaging and opt for using safe and suitable HDPE or other plastic packaging for their products. [ABSTRACT FROM AUTHOR]

In the scientific literature data analysis results are often presented when samples from different experiments or different conditions, technical replicates or times series are merged to increase the sample size before calculating the correlation coefficient. This way of proceeding violates two basic assumptions underlying the use of the correlation coefficient: sampling from one population and independence of the observations (independence of errors). Since correlations are used to measure and infer associations between biological entities, this has tremendous implications on the reliability of scientific results, as the violation of these assumption leads to wrong and biased results. In this technical note, I review some basic properties of the Pearson's correlation coefficient and illustrate some exemplary problems with simulated and experimental data, taking a didactic approach with the use of supporting graphical examples. [ABSTRACT FROM AUTHOR]

We study rank‐based approaches to estimate the correlation between two right‐censored variables. With end‐of‐study censoring, it is often impossible to nonparametrically identify the complete bivariate survival distribution, and therefore it is impossible to nonparametrically compute Spearman's rank correlation. As a solution, we propose two measures that can be nonparametrically estimated. The first measure is Spearman's correlation in a restricted region. The second measure is Spearman's correlation for an altered but estimable joint distribution. We describe population parameters for these measures and illustrate how they are similar to and different from the overall Spearman's correlation. We propose consistent estimators of these measures and study their performance through simulations. We illustrate our methods with a study assessing the correlation between the time to viral failure and the time to regimen change among persons living with HIV in Latin America who start antiretroviral therapy. [ABSTRACT FROM AUTHOR]

• Environmental, economic, and energy optimization of the ORC-VCR system. • A novel multi-objective optimization using the evaluation of distance from the average solution (EDAS) has been provided along with the improvements observed and comparison to grey relational analysis. • Results indicate that the isentropic efficiency of the compressor at 0.81 and of the expander at 0.86 were desirable, along with the following parametric settings. • Optimal cooling water inlet temperature at 312 K, the chilled fluid outlet temperature at 275 K. • The inlet temperature of the heat source at 392 K with R600 working fluid. The study performs multi-dimensional decision-making using the Evaluation of Distance from Average Solution (EDAS) with improved entropy weighting applied to figure out the best configuration for the ORC-VCR arrangement from a thermo-economic and environmental perspective. It is intended to maintain the operation of ORC-VCR's complete energy efficiency alongside producing minimal environmental impact. Besides EDAS, grey relational analysis has been conducted for an effective and precise determination of non-naïve operation controls. Moreover, objectively a novel cross-judgemental analysis has been implemented to measure the difference in opinion (DIO) between grey relational analysis and EDAS. The study has concluded in 30 % improvement in the desirability score of optimal operational setting for the ORC-VCR arrangement through EDAS. Judgemental analysis has proved the significance of EDAS from the perspective of a popular method like grey relational analysis, projecting a < 10 % DIO. [ABSTRACT FROM AUTHOR]

Process (systematic) variations of sub-5-nm node fin field-effect transistors (FinFETs) and nanosheet field-effect transistors (NSFETs) were investigated thoroughly using fully calibrated TCAD. All the process parameters consisting of front-end- as well as middle-of-line structure were independently randomized within feasible process conditions. A novel process scheme called source/drain patterning (SDP), having a superior performance by decreasing outer fringing capacitance through the downsized source/drain (S/D) epi, has also been analyzed for the variability study. SDP FinFETs have smaller variations of threshold voltages (Vth) , OFF-state currents (IOFF) , and effective currents (Ieff) than conventional ones because the subfin leakage is effectively controlled by bottom oxide (BO) beneath the source/drain instead of high punchthrough-stopper doping. The Spearman’s correlation results between process parameters, IOFF , and Ieff , showed that the process parameters affecting the short-channel effects vary IOFF and Ieff greatly. Especially, the most critical one was the fin width (Wfin) for FinFETs. SDP NSFETs have the smallest variations of Vth , IOFF , and Ieff. The BO blocks the bottom leakage completely, and the variations of nanosheet (NS) thickness (TNS) are much smaller than those of Wfin due to the different process flows: epitaxial growth for TNS versus patterning for Wfin. Therefore, NSFETs are promising to reduce the variations of Vth , IOFF , and Ieff in the sub-5-nm node. [ABSTRACT FROM AUTHOR]

Abstract.In his seminal work, Chatterjee (2021) introduced a novel correlation measure that is distribution-free, asymptotically normal, and consistent against all alternatives. In this article, we study the probabilistic relationships between Chatterjee’s correlation and the widely used Spearman’s correlation. We show that, under independence, the two sample-based correlations are asymptotically joint normal and asymptotically independent. Under dependence, the magnitudes of two correlations can be substantially different. We establish some extreme cases featuring large differences between these two correlations. Motivated by these findings, a new independence test is proposed by combining Chatterjee’s and Spearman’s correlations into a maximal strength measure of variable association. Our simulation study and real-data application show the good sensitivity of the new test to different correlation patterns. [ABSTRACT FROM AUTHOR]

Abstract We study locating propagation source in complex networks. We proposed an universal algorithm, which can accurately locate source of different propagation dynamics by using sparse observations. Without knowing the propagation dynamics and any parameters, we calculate Spearman centrality based on the character that positive correlation between inform time of nodes and geodesic distance between nodes and source. The algorithm have high location accuracy with low time complexity and can accurately infer initial time of source. All simulations on both model and real-world networks proved the feasibility and validity of this algorithm. Highlights • We proposed a universal source localization method for different propagation dynamics. • The proposed method can accurately locate source without knowing what kind of propagation dynamics. • We study the influence of parameters of propagation dynamics and properties of networks on locating accuracy. • The proposed method has low complexity. • We proposed a method for inferring initial time of source without knowing what kind of propagation dynamics and any parameters. [ABSTRACT FROM AUTHOR]

Spatio‐temporal variability in the observed diurnal temperature range (DTR) for the recent 30‐year period (1986–2015) is examined from a total of 18 weather stations in Hindukush Karakoram Himalaya region of northern Pakistan (HKNP). The daily maximum and minimum temperature data are used to compute the regional DTR, whereas observed total cloud cover (TCC) is used to assess its possible relationship with regional DTR, both on seasonal and annual basis. The regional mean DTR is 13.27 °C on annual basis, with a maximum in autumn (14.63 °C) and minimum in winter (11.81 °C). On annual basis, the regional DTR has increased significantly at a rate of .34 °C/decade, during the 30‐year study period at p ≤ .05, based on Mann–Kendall test. On seasonal basis, the DTR displays an increasing trend in all four seasons with largest significant increase in the winter season at a rate of .32 °C/decade. The DTR is positively correlated with maximum temperature of the region on seasonal and annual basis. Strong negative correlation is found between the DTR and observed TCC in all seasons, indicating that variability in TCC has an impact on the variation of DTR in this region. The statistically significant increasing DTR trend along with statistically significant decreasing trend of TCC in spring season suggests an early melt of snow and ice covers in the region, consequently changing the hydrological cycle of the region that demands a better water resource management in the HKNP. [ABSTRACT FROM AUTHOR]

The adoption of natural ventilation is prevalent in semi-open hotel lobbies on the tropical island of Hainan, China. This paper presents the results of a thermal comfort study of such applications in ten luxury hotels in this region. Significant differences were found between the local residents and tourists in their thermal satisfaction and between the males and females in their thermal comfort. Moreover, the thermal satisfaction levels of the local residents and tourists showed significant correlations with the wind speed and air temperature considering the wind speed compensation, with regard to genders, the males’ thermal comfort levels showed significant correlations with the wind speed and air temperature considering the wind speed compensation, while the females’ thermal comfort levels showed significant correlations with air temperature, wind speed and the air temperature considering the wind speed compensation. And results of ordinal logistic regression show that the tourists are more sensitive to the wind speed and air temperature considering the wind speed compensation than the local residents, and the females are more sensitive to the air temperature, wind speed and air temperature considering the wind speed compensation than the males. [ABSTRACT FROM AUTHOR]

This study examines the use of policy issues within horse-race coverage of the 2012 presidential election to determine how such issues were reported in two national newspapers. [ABSTRACT FROM AUTHOR]

Characterizations of fatty acids composition in % of total methylester of fatty acids (FAMEs) of fourteen vegetable oils--safflower, grape, silybum marianum, hemp, sunflower, wheat germ, pumpkin seed, sesame, rice bran, almond, rapeseed, peanut, olive, and coconut oil--were obtained by using gas chromatography (GC). Saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA), palmitic acid (C16:0; 4.6%-20.0%), oleic acid (C18:1; 6.2%-71.1%) and linoleic acid (C18:2; 1.6%-79%), respectively, were found predominant. The nutritional aspect of analyzed oils was evaluated by determination of the energy contribution of SFAs (19.4%-695.7% ERDI), PUFAs (10.6%-786.8% ERDI), n-3 FAs (4.4%-117.1% ERDI) and n-6 FAs (1.8%-959.2% ERDI), expressed in % ERDI of 1 g oil to energy recommended dietary intakes (ERDI) for total fat (ERDI--37.7 kJ/g). The significant relationship between the reported data of total fat, SFAs, MUFAs and PUFAs intakes (% ERDI) for adults and mortality caused by coronary heart diseases (CHD) and cardiovascular diseases (CVD) in twelve countries has not been confirmed by Spearman's correlations. [ABSTRACT FROM AUTHOR]

The main aim of this paper was to identify independent variables that explain the dependent variable of the inbound mobility rate in the four countries from the Visegrad Group. The statistical data of 5 years from 2008 to 2012 were analysed. In order to verify the hypotheses, Spearman's correlation coefficient and an analysis of variance test with post-hoc Tukey test were applied. The results indicate that there does not exist one precise set of variables that could explain the academic attractiveness of each host country of the Visegrad Group. Furthermore, there exist statistically significant differences between the Visegrad Countries in respect of their attractiveness for foreign students, which was expressed by inbound mobility rate. The paper contributes to the literature by investigating the preconditions for national academic attractiveness. [ABSTRACT FROM AUTHOR]

In this paper, we study the empirical spectral distribution of Spearman's rank correlation matrices, under the assumption that the observations are independent and identically distributed random vectors and the features are correlated. We show that the limiting spectral distribution is the generalized Marc̆enko–Pastur law with the covariance matrix of the observation after standardized transformation. With these results, we compare several classical covariance/correlation matrices including the sample covariance matrix, Pearson's correlation matrix, Kendall's correlation matrix and Spearman's correlation matrix. [ABSTRACT FROM AUTHOR]

A direct-infusion electrospray ionization triple-quadrupole mass spectrometry method with multiple reaction monitoring ( MRM) was employed to measure 264 lipid analytes extracted from leaves of Arabidopsis thaliana subjected to mechanical wounding. The method provided precise measurements with an average coefficient of variation of 6.1%. Lipid classes analyzed comprised galactolipids and phospholipids (including monoacyl molecular species, molecular species with oxidized acyl chains, phosphatidic acids ( PAs)), tri- and tetra-galactosyldiacylglycerols ( Tr GDGs and Te GDGs), head-group-acylated galactolipids, and head-group-acylated phosphatidylglycerol (ac PG), sulfoquinovosyldiacylglycerols ( SQDGs), sphingolipids, di- and tri-acylglycerols ( DAGs and TAGs), and sterol derivatives. Of the 264 lipid analytes, 254 changed significantly in response to wounding. In general, levels of structural lipids decreased, whereas monoacyl molecular species, galactolipids and phosphatidylglycerols ( PGs) with oxidized fatty acyl chains, PAs, Tr GDGs, Te GDGs, TAGs, head-group-acylated galactolipids, ac PG, and some sterol derivatives increased, many transiently. The observed changes are consistent with activation of lipid oxidizing, hydrolyzing, glycosylating, and acylating activities in the wounding response. Correlation analysis of the levels of lipid analytes across individual control and treated plants was used to construct a lipid dendrogram and to define clusters and sub-clusters of lipid analytes, each composed of a group of lipids which occurred in a coordinated manner. Current knowledge of metabolism supports the notion that observed sub-clusters comprise lipids generated by a common enzyme and/or metabolically downstream of a common enzyme. This work demonstrates that co-occurrence analysis, based on correlation of lipid levels among plants, is a powerful approach to defining lipids generated in vivo by a common enzymatic pathway. [ABSTRACT FROM AUTHOR]

This paper investigated the agglomerating and wetting behaviour during coal dust suppression via the synergistic application of hydrocarbon and short-chain-fluorocarbon surfactants in the presence of electrolytes. A maximum 51.01% and 53.12% reduction in surface tension is achieved after compounding FS-50 and FS-3100 with SDBS and FMEE. Short-chain fluorocarbon surfactants reduced the immersing time of coal particles from maximum 637.03 s to minimum 28.06 s, and further diminished to 9.33 s in the presence of electrolytes. The addition of short-chain fluorocarbon and electrolytes can significantly promote the agglomeration behaviour among treated coal particles. After the addition of NaCl and NaAc, the maximum dust suppression rate reaches 95.12%, which is 1.21–1.33 times of binary surfactants and 1.59–2.01 times of the solely application of hydrocarbon ones. The agglomerating behaviour is more sufficient in predicting the dust suppression rate. The larger the coal particles, the higher liquid bridge force and stronger agglomerated coal particle clusters. [Display omitted] • Over 53.12% reduction in surface tension is achieved after adding FSs. • The addition of electrolyte can further reduce the surface tension to another 12%. • Electrolytes can significantly improve both wettability and agglomeration ability. • Ternary solution achieves 1.59–2.01times improvement on dedusting rate. • Spearman's correlation confirms higher consistency between TSI and dedusting rate. [ABSTRACT FROM AUTHOR]

The objective of this work was to study different adaptability and stability methodologies and verify that the joint use of these methodologies can provide greater reliability in the selection of Pennisetum sp. clones to the forage yield. It was evaluated eight Pennisetum spp. clones (Taiwan A-146 2.37, Taiwan A-146 2.27, Taiwan-146 2,114, Merker Mexico MX 6.31, Mott, HV-241, and 'Elephante B' and IRI-381). The methods used to study the adaptability and stability were Eberhart and Russell, Wricke and Lin and Binns. The HV-241 clone, despite its adaptability to favorable environments, showed the lowest yield stability. The best performing were Taiwan A-146 2.37 and 'Elefante B' genotype, however, the former is suitable for favorable environments and the latter to unfavorable environments. The evaluation of Pennisetum spp. clones through different adaptability and stability methodologies to the forage yield allowed for greater characterization of productive performance of the clones and can provide greater reliability to the selection. [ABSTRACT FROM AUTHOR]

DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association approaches, namely Pearson's correlation, Spearman's correlation and Hoeffding's D measure, we aimed at assessing the most approppriate one for each purpose. Using simulations, we demonstrate that the Hoeffding's D measure outperforms Pearson's and Spearman's approaches in identifying nonlinear associations. Our results demonstrate that Hoeffding's D measure is less sensitive to outliers and is a more powerful tool to identify nonlinear and non-monotonic associations. We have also applied Hoeffding's D measure in order to identify new putative genes associated with tp53. Therefore, we propose the Hoeffding's D measure to identify nonlinear associations between gene expression profiles. [ABSTRACT FROM AUTHOR]

Most Western-European countries exceed the critical loads for nitrogen (N) losses. High nitrogen (N) inputs make agriculture one of the largest contributors to N pollution. There might be a potential to reduce this losses with an output tax on animal products, as they have low N use efficiency and a tax has the potential to reduce the consumption of this products. We want to assess the potential of a food tax on animal products to reduce the N surplus of Swiss agriculture. We implemented a tax on meat and a tax on milk and meat in the agent-based model SWISSland. The model combines an agent-based model with a microeconomic model at the farm scale. To better understand the low response of the food tax, we applied in a second step a robust two-step global sensitivity analysis of abatement costs of individual model agents. Imposing a tax led to an N surplus reduction of 2.1% where only meat was taxed and 2.3% where both milk and meat were taxed. The sensitivity analysis showed that distinct agents reacted non-uniformly to changing prices, so that the effect of the tax was sometimes even cancelled out. This calls for more differentiated policies to reduce the negative impact of N losses. The overall impact of the food tax was minor as the distinct agents react not uniformly to lower producer prices. [Display omitted] • Nitrogen surpluses of Swiss agriculture remain on a high level since the 90's. • We assessed the effects of a food tax on nitrogen surplus in the agent-based model SWISSland. • Food taxes on milk and meat products reduced nitrogen surpluses by 2.1% to 2.3%, respectively. • A robust sensitivity analysis on different model agents revealed that distinct agents react differently to varying prices. • Food taxes are not effective to reduce nitrogen surpluses as distinct farms react non-uniform to changing prices. [ABSTRACT FROM AUTHOR]

This article attempts to model interdependencies between socio-economic, energy, and environmental factors with selected data characterizing the development of the hydrogen economy. The study applies Spearman's correlation and a linear regression model to estimate the influence of gross domestic product, population, final energy consumption, renewable energy, and CO2 emission on chosen hydrogen indicators—production, patents, energy technology research, development, and demonstration budgets. The study was conducted in nine countries selected for their actions towards a hydrogen economy based on analyses of national strategies, policies, research and development programs, and roadmaps. The results confirm the statistically significant impact of the chosen indicators, which are the drivers for the development of the hydrogen economy from 2008 to 2018. Moreover, the empirical results show that different characteristics in each country contribute to the development of the hydrogen economy vision. [ABSTRACT FROM AUTHOR]

• The heteroscedastic multi-breed model with Student's t-distribution is the most appropriate for the national genetic evaluation of the Girolando breed for test-day milk yield. • The flexibility of the heteroscedastic model has a different effect on the sires in the 3/4H genetic group, when compared to 5/8H group. • These results support the implementation of robust models that account for sources of heteroscedasticity. The objective was to identify the best multi-breed model for the genetic evaluation of test-day milk yield (TDMY) in a Girolando population. The observations were measured from 2000 to 2014, totaling 122,507 observations of 13,544 first-lactation cows and a complete kinship matrix of 66,384 animals. Four different methodologies were evaluated: homoscedastic or heteroscedastic multi-breed model with Gaussian destruction (MAM-G-Ho or MAM-G-He) and homoscedastic or heteroscedastic multi-breed model with Student's t-distribution (MAM-T-Ho or MAM-T-He). The criteria for choosing the best model were the deviance information criterion (DIC), deviance based on the Conditional Predictive Ordinate (DCPO), and deviance based on the Bayes factors (DBF). According to the selection criteria, the MAM-T-He presented the lowest values of DIC, DCPO, and DBF, indicating a better quality of fit for the population in question. Heritability estimates were of medium magnitude for TDMY, varying from 0.27±0.02 to 0.39±0.03 in the different models. Spearman's correlations based on estimated breeding values used to compare the ranking of animals between Student's t and Gaussian models were low (0.63 to 0.72) when considering all sires or when considering 10, 20, or 30% of the best sires. These results support the implementation of robust models that account for sources of heteroscedasticity to increase the accuracy of genetic evaluations in the multi-breed population of the Girolando breed. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus disease 2019 (COVID-19), by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has quickly developed into a worldwide pandemic. Mutations in the SARS-CoV-2 genome may affect various aspects of the disease including fatality ratio. In this study, 553,518 SARS-CoV-2 genome sequences isolated from patients from continents for the period 1 December 2020 to 15 March 2021 were comprehensively analyzed and a total of 82 mutations were identified concerning the reference sequence. In addition, associations between the mutations and the case fatality ratio (CFR), cases per million and deaths per million, were examined. The mutations having the highest frequencies among different continents were Spike_D614G and NSP12_P323L. Among the identified mutations, NSP2_T153M, NSP14_I42V and Spike_L18F mutations showed a positive correlation to CFR. While the NSP13_Y541C, NSP3_T73I and NSP3_Q180H mutations demonstrated a negative correlation to CFR. The Spike_D614G and NSP12_P323L mutations showed a positive correlation to deaths per million. The NSP3_T1198K, NS8_L84S and NSP12_A97V mutations showed a significant negative correlation to deaths per million. The NSP12_P323L and Spike_D614G mutations showed a positive correlation to the number of cases per million. In contrast, NS8_L84S and NSP12_A97V mutations showed a negative correlation to the number of cases per million. In addition, among the identified clades, none showed a significant correlation to CFR. The G, GR, GV, S clades showed a significant positive correlation to deaths per million. The GR and S clades showed a positive correlation to number of cases per million. The clades having the highest frequencies among continents were G, followed by GH and GR. These findings should be taken into consideration during epidemiological surveys of the virus and vaccine development. [ABSTRACT FROM AUTHOR]