scholarly journals Measurement of flow harmonics correlations with mean transverse momentum in lead–lead and proton–lead collisions at $$\sqrt{s_{\mathrm{NN}}} = 5.02~\hbox {TeV}$$ with the ATLAS detector

2019 ◽  
Vol 79 (12) ◽  
Author(s):  
G. Aad ◽  
◽  
B. Abbott ◽  
D. C. Abbott ◽  
A. Abed Abud ◽  
...  
Keyword(s):  
Charged Particle ◽  
Transverse Momentum ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Gluon Plasma ◽  
Pearson Correlation Coefficient ◽  
Order Flow ◽  
Momentum Range ◽  
Ion Collisions

AbstractTo assess the properties of the quark–gluon plasma formed in ultrarelativistic ion collisions, the ATLAS experiment at the LHC measures a correlation between the mean transverse momentum and the flow harmonics. The analysis uses data samples of lead–lead and proton–lead collisions obtained at the centre-of-mass energy per nucleon pair of 5.02 TeV, corresponding to total integrated luminosities of $$22~\upmu \text {b}^{-1}$$22μb-1 and $$28~\text {nb}^{-1}$$28nb-1, respectively. The measurement is performed using a modified Pearson correlation coefficient with the charged-particle tracks on an event-by-event basis. The modified Pearson correlation coefficients for the 2nd-, 3rd-, and 4th-order flow harmonics are measured in the lead–lead collisions as a function of event centrality quantified as the number of charged particles or the number of nucleons participating in the collision. The measurements are performed for several intervals of the charged-particle transverse momentum. The correlation coefficients for all studied harmonics exhibit a strong centrality evolution, which only weakly depends on the charged-particle momentum range. In the proton–lead collisions, the modified Pearson correlation coefficient measured for the 2nd-order flow harmonics shows only weak centrality dependence. The lead-lead data is qualitatively described by the predictions based on the hydrodynamical model.

Assessing the Motor Status Score: A Scale for the Evaluation of Upper Limb Motor Outcomes in Patients after Stroke

2002 ◽  
Vol 16 (3) ◽  
pp. 283-289 ◽  
Author(s):  
Mark Ferraro ◽  
Jennifer Hogan Demaio ◽  
Jennifer Krol ◽  
Chris Trudell ◽  
Keren Rannekleiv ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Upper Limb ◽  
Pearson Correlation ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Pearson Correlation Coefficient ◽  
Maximum Score ◽  
Intraclass Correlation Coefficients ◽  
Upper Extremity Impairment ◽  
Motor Outcomes

The Motor Status Scale (MSS) measures shoulder, elbow (maximum score = 40), wrist, hand, and finger movements (maximum score = 42), and expands the measurement of upper extremity impairment and disability provided by the Fugl-Meyer (FM) score. This work examines the interrater reliability and criterion validity of the MSS performed in patients admitted to a rehabilitation hospital 21 ± 4 days after stroke. Using the MSS and the FM, 7 occupational therapists masked to each other’s judgments, evaluated 12 consecutive patients with stroke. Two therapists evaluated 6 additional patients on consecutive days. Intraclass correlation coefficients were significant for each group of raters for the shoulder/elbow and for the wrist/hand (P < 0.0001); test-retest measures were also significant for the shoulder/elbow (Pearson correlation coefficient r = 0.99, P < 0.004) and for the wrist/hand (Pearson correlation coefficient r = 0.99, P < 0.003). The internal item consistency for the overall MSS was significant (Cronbach alpha = 0.98, P < 0.0001). Finally the correlation between the MSS and the FM (R 2 = 0.964) was significant (P < 0.0001). The MSS affords a reliable and valid assessment of upper limb impairment and disability following stroke.

scholarly journals Methods of Estimating Correlation Coefficients in the Presence of Influential Outlier(s)

2021 ◽  
Vol 4 (3) ◽  
pp. 157-185
Author(s):  
Etaga H.O. ◽  
Okoro I. ◽  
Aforka K.F. ◽  
Ngonadi L.O.
Keyword(s):  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pearson Correlation Coefficient ◽  
Spearman Correlation ◽  
Correlation Methods ◽  
Linear Relationships ◽  
Median Correlation ◽  
Standing Problem ◽  
Research Analysis

Correlation methods are indispensable in the study of the linear relationship between two variables. However, many researchers often adopt inappropriate correlation methods in the study of linear relationships which usually leads to unreliable results. Recurrently, most researchers ignorantly employ the Pearson method in a dataset that contained outliers, instead of more appropriate correlation methods such as Spearman, Kendall Tau, Median and Quadrant which might be suitable in the calculation of correlation coefficient in the presence of influential outliers. It is noted that the accuracy of estimation of correlation coefficients under outliers has been a long-standing problem for methodological researchers. This is due to low knowledge of correlation methods and their assumptions which have led to inappropriate application of correlation methods in research analysis. Five different methods of estimating correlation coefficients in the presence of influential outlier (contaminated data) were considered: Pearson Correlation Coefficient, Spearman Correlation Coefficient, Kendall Tau Correlation Coefficient, Median Correlation Coefficient and Quadrant Correlation Coefficient.

Single- versus multiple-item assessment of quality of life in patients with advanced cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e20528-e20528
Author(s):  
S. H. Bush ◽  
H. A. Parsons ◽  
J. L. Palmer ◽  
R. Chacko ◽  
Z. Li ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Regression Analysis ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Well Being ◽  
Pearson Correlation Coefficient ◽  
Spearman Correlation ◽  
Symptom Intensity

e20528 Background: The main objective of palliative cancer care is to improve quality of life (QOL). As multiple dimensions impact on the construct of QOL, multi-dimensional instruments are usually used in its measurement. These are time consuming and burdensome for repeated use. Recent authors have suggested that brief single-item global assessments can provide a reliable measure of QOL. We assessed the performance of the Edmonton Symptom Assessment System ‘feeling of well-being’ item (ESAS WB) using the Functional Assessment of Cancer Therapy - General (FACT-G) instrument as a gold standard. Methods: After obtaining IRB approval, we reviewed the data from 213 advanced cancer patients who had participated in six studies from March 2006 to June 2008 and determined the level of association between baseline ESAS WB and FACT-G total score and subscale domains (Physical (Pwb), Social/Family (Swb), Emotional (Ewb), and Functional (Fwb) Well-Being) and also the 9 ESAS symptom intensity scores using Spearman correlation coefficients. We also calculated the change between the baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score and determined their level of association using a Pearson correlation coefficient. In addition, we predicted the change in FACT-G as predicted by the change in ESAS WB score using regression analysis. Results: Mean age was 60 (SD 12) years and 48% were female. At T1, the Spearman correlation coefficient of ESAS WB and FACT-G was -0.48 (p<0.0001). Spearman correlation coefficients for ESAS WB and FACT-G subscale domains and ESAS symptom intensity scores were also highly significant (p<0.0001) for all physical and emotional symptoms (other than p=0.003 for nausea) except for FACT Swb (p=0.08). The Pearson correlation coefficient for difference between T1 and T2 in ESAS WB and FACT-G for 146 patients was -0.36 (p<0.0001). The regression analysis was highly significant (p<0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference (MID) was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. Conclusions: ESAS WB is a practical instrument for clinical use and best reflects the Pwb, Ewb and Fwb domains of FACT-G as compared to Swb. No significant financial relationships to disclose.

Inter- and intra-observer reliability of quantitative sensory testing performed with the SMall animal ALGOmeter (SMALGO) to evaluate pain associated with feline gingivostomatitis

2019 ◽  
Vol 22 (4) ◽  
pp. 271-276 ◽  
Author(s):  
Hanna Machin ◽  
Serena Pevere ◽  
Chiara Adami
Keyword(s):  
Correlation Coefficient ◽  
Quantitative Sensory Testing ◽  
Statistical Tests ◽  
Pearson Correlation ◽  
Small Animal ◽  
Correlation Coefficients ◽  
Pearson Correlation Coefficient ◽  
Sensory Testing ◽  
Observer Reliability ◽  
Mechanical Thresholds

Objectives The aim of this study was to evaluate the inter- and intra-observer reliability of quantitative sensory testing performed with the SMall animal ALGOmeter (SMALGO) in healthy cats and in cats with chronic gingivostomatitis (CGS), and to evaluate the SMALGO as a tool to detect and quantify pain in cats with CGS. Methods Thirty cats from a private shelter were included and assigned to one of two groups: group C (healthy cats; n = 15) or group CGS (cats with CGS; n = 15). In all cats the mechanical thresholds were measured with the SMALGO, with the sensor tip applied to the superior lip above the canine root, by two independent investigators (A, experienced; B, unexperienced), on two different occasions (day 1 and day 2) with a 24 h interval. A CGS scale was used in the diseased cats to assess the severity of the condition. For the reliability analysis, intra-class correlation coefficients (ICCs) were calculated. Other statistical tests used were Pearson correlation coefficient and a paired t-test. Results The inter- and intra-observer levels of agreement were fair (ICC = 0.50) and good, respectively (ICC = 0.73 for investigator A; ICC = 0.60 for investigator B). However, the thresholds measured in healthy cats (169 ± 59 g) did not differ from those obtained from diseased cats (156 ± 82 g; P = 0.35). There was no correlation between the scores of the CGS scale and the thresholds measured in diseased cats (Pearson correlation coefficient = 0.047; P = 0.87). Conclusions and relevance Quantitative sensory testing performed with the SMALGO in cats is repeatable and reliable, regardless of the expertise of the investigator. However, the findings of this study suggest that the mechanical thresholds measured with the SMALGO may not be a valuable indicator of pain in cats with CGS.

Identifying the Source of Weathered Petroleum: Matching Infrared Spectra with Correlation Coefficients

1977 ◽  
Vol 31 (6) ◽  
pp. 524-527 ◽  
Author(s):  
Carl D. Baer ◽  
Chris W. Brown
Keyword(s):  
Correlation Coefficient ◽  
Similarity Measure ◽  
Infrared Spectra ◽  
Nearest Neighbor ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pearson Correlation Coefficient ◽  
K Nearest Neighbor ◽  
Data Set ◽  
Novel Method

A novel method is presented for identifying the source of weathered petroleum by measuring the similarity between the spectrum of a weathered oil and spectra of artificially weathered samples. The Pearson correlation coefficient is used as the similarity measure, and three separate K-nearest neighbor approaches are tested on the data set.

scholarly journals Measuring the Relationship of Bivariate Data Using Hodges-Lehman Estimator

2020 ◽  
pp. 1-5
Author(s):  
Suhaida Abdullah ◽  
Nur Amira Zakaria ◽  
Nor Aishah Ahad ◽  
Norhayati Yusof ◽  
Sharipah Soaad Syed Yahaya
Keyword(s):  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Median Absolute Deviation ◽  
Poor Correlation ◽  
Pearson Correlation Coefficient ◽  
Absolute Deviation ◽  
Bivariate Data ◽  
Relationship Of ◽  
The Relationship

The relationship of bivariate data ordinarily measured using correlation coefficient. The most commonly used correlation coefficient is the Pearson correlation coefficient. This coefficient is well-known as the best coefficient for interval or ratio bivariate data with a linear relationship. Even though this coefficient is good under the mentioned condition, it also becomes very sensitive to a small departure from linearity. Usually, this is because of the existence of an outlier. For that reason, this paper provides new robust correlation coefficients which combine the elements of nonparametric technique from the Hodges Lehmann estimator and the parametric technique based on the Pearson correlation coefficient. This paper also introduces different scale estimators such as median and median absolute deviation (MADn) and denoted by rHL(med) and rHL(MADn) respectively. The performance of the proposed correlation coefficients is measured by the coefficient values and these values are also being compared to the Pearson correlation coefficient and several existing robust correlation coefficients. The results show that the Pearson correlation coefficient (r) with no doubt is very good under perfect data condition, but with only 10% outliers, it not only give poor correlation value but turns the direction of the relationship to negative. While the rHL(med) and rHL(MADn) offer the highest coefficient values and these values are robust to the existence of outliers by up to 30%. With very good performance under all data conditions yet simple in the calculation, the rHL(med) and rHL(MADn) is considered a good alternative to the r when need to deal with outliers. Keywords: correlation coefficient; Hodges Lehmann; median; median absolute deviation (MADn)

Relationship between Invasive and Non-Invasive Hemodynamic Measures in Experimental Pulmonary Hypertension

2020 ◽  
Vol 16 (1) ◽  
pp. 47-53
Author(s):  
Vicente Benavides-Córdoba ◽  
Mauricio Palacios Gómez
Keyword(s):  
Heart Rate ◽  
Pulmonary Hypertension ◽  
Ejection Fraction ◽  
Right Ventricle ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Systolic Pressure ◽  
Control Group ◽  
Pearson Correlation Coefficient ◽  
Non Invasive

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.

scholarly journals Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 156
Author(s):  
Charles Carlson ◽  
Vanessa-Rose Turpin ◽  
Ahmad Suliman ◽  
Carl Ade ◽  
Steve Warren ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Stroke Volume ◽  
Systolic Blood Pressure ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Health Assessment ◽  
Initial Study ◽  
Pearson Correlation Coefficient ◽  
Medical Systems ◽  
Cardiovascular Parameters

Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms. Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters). Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/− 0.15), dP/dtmax (Pearson correlation coefficient of 0.51 +/− 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/− 0.17). Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume. Significance: To the best of the authors’ knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.

scholarly journals Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai
Keyword(s):  
South Africa ◽  
South African ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Pearson Correlation Coefficient ◽  
Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

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