scholarly journals Musical Mix Clarity Prediction Using Decomposition and Perceptual Masking Thresholds

2021 ◽  
Vol 11 (20) ◽  
pp. 9578
Author(s):  
Andrew Parker ◽  
Steven Fenton
Keyword(s):  
Rank Correlation ◽  
Model Output ◽  
Independent Dataset ◽  
Perceptual Model ◽  
Spearman’S Rank Correlation ◽  
Proposed Model ◽  
Close Relationship ◽  
Negative Effect ◽  
Perceptual Masking ◽  
Music Information

Objective measurement of perceptually motivated music attributes has application in both target-driven mixing and mastering methodologies and music information retrieval. This work proposes a perceptual model of mix clarity which decomposes a mixed input signal into transient, steady-state, and residual components. Masking thresholds are calculated for each component and their relative relationship is used to determine an overall masking score as the model’s output. Three variants of the model were tested against subjective mix clarity scores gathered from a controlled listening test. The best performing variant achieved a Spearman’s rank correlation of rho = 0.8382 (p < 0.01). Furthermore, the model output was analysed using an independent dataset generated by progressively applying degradation effects to the test stimuli. Analysis of the model suggested a close relationship between the proposed model and the subjective mix clarity scores particularly when masking was measured using linearly spaced analysis bands. Moreover, the presence of noise-like residual signals was shown to have a negative effect on the perceived mix clarity.

scholarly journals Activity Recommendation Model Using Rank Correlation for Chronic Stress Management

2019 ◽  
Vol 9 (20) ◽  
pp. 4284 ◽  
Author(s):  
Ji-Soo Kang ◽  
Dong-Hoon Shin ◽  
Ji-Won Baek ◽  
Kyungyong Chung
Keyword(s):  
Stress Management ◽  
Correlation Coefficient ◽  
Chronic Stress ◽  
Rank Correlation ◽  
Korean People ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Proposed Model ◽  
Basic Rank

Korean people are exposed to stress due to the constant competitive structure caused by rapid industrialization. As a result, there is a need for ways that can effectively manage stress and help improve quality of life. Therefore, this study proposes an activity recommendation model using rank correlation for chronic stress management. Using Spearman’s rank correlation coefficient, the proposed model finds the correlations between users’ Positive Activity for Stress Management (PASM), Negative Activity for Stress Management (NASM), and Perceived Stress Scale (PSS). Spearman’s rank correlation coefficient improves the accuracy of recommendations by putting a basic rank value in a missing value to solve the sparsity problem and cold-start problem. For the performance evaluation of the proposed model, F-measure is applied using the average precision and recall after five times of recommendations for 20 users. As a result, the proposed method has better performance than other models, since it recommends activities with the use of the correlation between PASM and NASM. The proposed activity recommendation model for stress management makes it possible to manage user’s stress effectively by lowering the user’s PSS using correlation.

scholarly journals Analysis of Six Bone-Derived Factors in Plasma and CSF of Chinese Patients with Parkinson's Disease

2020 ◽  
Author(s):  
Xiang Chen ◽  
Yuwan Lin ◽  
Chaojun Chen ◽  
Wenyuan Guo ◽  
Miaomiao Zhou ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Impairment ◽  
Rank Correlation ◽  
Chinese Patients ◽  
Secretory Proteins ◽  
Spearman’S Rank Correlation ◽  
Close Relationship ◽  
Two Factors ◽  
Antibody Arrays

Abstract Background: Parkinson's disease (PD) has a close relationship with osteoporosis and bone secretory proteins may be involved in disease progress. Objectives: To detect the six bone-derived factors in plasma and CSF of patients with PD and evaluate their correlations with CRP level, motor impairment and HY stage of the disease.Methods: We included 250 PD patients and 250 controls. Levels of OCN, OPN, OPG, SO, BMP2 and DKK-1 in Plasma and CSF were measured by custom protein antibody arrays. Data were analyzed using Mann-Whitney U-test and Spearman’s rank correlation. Results: Plasma levels of OCN and OPN were correlated with CRP level and HY stage and motor impairment of PD. Furthermore, the plasma assessment with CSF detection may enhance their potential prediction on PD.Conclusions: OCN and OPN may serve as potential biomarkers for PD. The inflammation response may be involved in the cross-talks between the two factors and PD.

scholarly journals Analysis of Six Bone-derived Factors in Plasma and Csf of Chinese Patients With Parkinson's Disease

2020 ◽  
Author(s):  
Xiang Chen ◽  
Yuwan Lin ◽  
Chaojun Chen ◽  
Wenyuan Guo ◽  
Miaomiao Zhou ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Impairment ◽  
Rank Correlation ◽  
Chinese Patients ◽  
Secretory Proteins ◽  
Spearman’S Rank Correlation ◽  
Close Relationship ◽  
Two Factors ◽  
Potential Biomarkers

Abstract BackgroundParkinson's disease (PD) has a close relationship with osteoporosis and bone secretory proteins may be involved in disease progress.ObjectivesTo detect the six bone-derived factors in plasma and CSFof patient swith PD and evaluate their correlations with CRP level, motor impairment and HY stage of the disease.MethodsWe included 250 PD patients and 250 controls. Levels of OCN, OPN,OPG, SO, BMP2 andDKK-1 in Plasma and CSF were measured by custom protein antibody arrays.Data were analyzed using Mann-Whitney U-testand Spearman’s rank correlation.ResultsPlasma levels of OCN and OPN were correlated with CRP level and HY stage and motor impairment of PD.Furthermore, the plasma assessment with CSF detection may enhance their potential prediction on PD.ConclusionsOCN and OPN may serve as potential biomarkers for PD. The inflammation response may be involved in the cross-talks between the two factors and PD.

A Study of the Relationships between Nursing Students’ Meanings of Life, Positive Beliefs, and Well-Being

2018 ◽  
Vol 3 (01) ◽  
Author(s):  
Fu-Ju Tsai ◽  
Cheng-Yu Chen ◽  
Gwo-Liang Yeh ◽  
Yih-Jin Hu ◽  
Chie-Chien Tseng ◽  
...  
Keyword(s):  
Health Promotion ◽  
Nursing Students ◽  
Analysis Of Variance ◽  
Rank Correlation ◽  
Meaning Of Life ◽  
Well Being ◽  
Social Health ◽  
Cross Sectional ◽  
Nursing Educators ◽  
Spearman’S Rank Correlation

Background: Nursing educators should train nursing students to pursue physical, psychological, spiritual, and social health promotion. The purpose of this study was to explore relationships between nursing students’ meaning of life, positive beliefs, and well-being. Methods: A cross-sectional correlational study with a quantitative approach was adopted. Purposive sampling was used. A total of 170 nursing students voluntarily participated in this study. A 56-item questionnaire was used to examine nursing students’ meaning of life (1-25 items), positive beliefs (1-11 items), and well-being (1-20 items). The content validity index (CVI) of the study questionnaire was established as 0.95 by seven expert scholars. The reliability values for the three parts of the measure were as follows: meaning of life, Cronbach’s α 0.96; positive beliefs, Cronbach’s α 0.93; and well-being, Cronbach’s α 0.95. Percentages, frequencies, means, SDs, Kruskal-Wallis one-way analysis of variance by rank, Spearman’s rank correlation, one-way analysis of variance, Spearman’s rho correlation, and regression analysis were used for the data analysis. Results: Nursing students had the following mean scores: meaning of life with 4.02 (SD 0.56); positive beliefs with 3.92 (SD 0.62); and well-being with 3.95 (SD 0.57). The results indicate that for all nursing students, meaning of life was positively correlated with positive beliefs, r=0.83 (P<.01); similarly, all nursing students had positive beliefs that were positively correlated with meaning of life, r=0.83 (P<.01). In the results of the study, the nursing students’ background, meaning of life and positive beliefs explained 63% of the variance in well-being (Adjusted R2 squared =0.63, F=33.41, P<.001). Conclusions: Nursing students’ sense of meaning of life and positive beliefs may impact their well-being. Therefore, nursing educators can promote meaning of life and positive beliefs to nursing students as a way to increase their well-being for physical, psychological, spiritual, and social health promotion.

scholarly journals Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Hui Jiang ◽  
Peian Lou ◽  
Xiaoluo Chen ◽  
Chenguang Wu ◽  
Shihe Shao
Keyword(s):  
Roc Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Rank Correlation ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Biological Functions ◽  
Multivariate Logistic Regression ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient

Abstract Background Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown. Methods Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman’s rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. Results The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman’s rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively). Conclusion The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.

scholarly journals 4mCPred-CNN—Prediction of DNA N4-Methylcytosine in the Mouse Genome Using a Convolutional Neural Network

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 296
Author(s):  
Zeeshan Abbas ◽  
Hilal Tayara ◽  
Kil To Chong
Keyword(s):  
Mouse Genome ◽  
Matthews Correlation Coefficient ◽  
Biological Functions ◽  
Independent Dataset ◽  
Validation Test ◽  
Single Feature ◽  
Proposed Model ◽  
Dna Modifications ◽  
Feature Encoding ◽  
Feature Encoding Scheme

Among DNA modifications, N4-methylcytosine (4mC) is one of the most significant ones, and it is linked to the development of cell proliferation and gene expression. To know different its biological functions, the accurate detection of 4mC sites is required. Although we have several techniques for the prediction of 4mC sites in different genomes based on both machine learning (ML) and convolutional neural networks (CNNs), there is no CNN-based tool for the identification of 4mC sites in the mouse genome. In this article, a CNN-based model named 4mCPred-CNN was developed to classify 4mC locations in the mouse genome. Until now, we had only two ML-based models for this purpose; they utilized several feature encoding schemes, and thus still had a lot of space available to improve the prediction accuracy. Utilizing only a single feature encoding scheme—one-hot encoding—we outperformed both of the previous ML-based techniques. In a ten-fold validation test, the proposed model, 4mCPred-CNN, achieved an accuracy of 85.71% and Matthews correlation coefficient (MCC) of 0.717. On an independent dataset, the achieved accuracy was 87.50% with an MCC value of 0.750. The attained results exhibit that the proposed model can be of great use for researchers in the fields of biology and bioinformatics.

scholarly journals Magnetic resonance cisternography imaging findings related to the leakage of Gadolinium into the subarachnoid space

2021 ◽  
Author(s):  
Rei Nakamichi ◽  
Toshiaki Taoka ◽  
Hisashi Kawai ◽  
Tadao Yoshida ◽  
Michihiko Sone ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Subarachnoid Space ◽  
Area Under The Curve ◽  
Rank Correlation ◽  
Predictive Performance ◽  
Roc Curves ◽  
Imaging Findings ◽  
Spearman’S Rank Correlation ◽  
Sagittal Sinus ◽  
Magnetic Resonance Cisternography

Abstract Purpose To identify magnetic resonance cisternography (MRC) imaging findings related to Gadolinium-based contrast agent (GBCA) leakage into the subarachnoid space. Materials and methods The number of voxels of GBCA leakage (V-leak) on 3D-real inversion recovery images was measured in 56 patients scanned 4 h post-intravenous GBCA injection. Bridging veins (BVs) were identified on MRC. The numbers of BVs with surrounding cystic structures (BV-cyst), with arachnoid granulations protruding into the superior sagittal sinus (BV-AG-SSS) and the skull (BV-AG-skull), and including any of these factors (BV-incl) were recorded. Correlations between these variables and V-leak were examined based on the Spearman’s rank correlation coefficient. Receiver-operating characteristic (ROC) curves were generated to investigate the predictive performance of GBCA leakage. Results V-leak and the number of BV-incl were strongly correlated (r = 0.609, p < 0.0001). The numbers of BV-cyst and BV-AG-skull had weaker correlations with V-leak (r = 0.364, p = 0.006; r = 0.311, p = 0.020, respectively). The number of BV-AG-SSS was not correlated with V-leak. The ROC curve for contrast leakage exceeding 1000 voxels and the number of BV-incl had moderate accuracy, with an area under the curve of 0.871. Conclusion The number of BV-incl may be a predictor of GBCA leakage and a biomarker for waste drainage function without using GBCA.

scholarly journals Predicting presenteeism using measures of health status

2021 ◽  
Author(s):  
Cheryl Jones ◽  
Katherine Payne ◽  
Alexander Thompson ◽  
Suzanne M. M. Verstappen
Keyword(s):  
Health Status ◽  
Online Survey ◽  
Activity Index ◽  
Work Productivity ◽  
Rank Correlation ◽  
Ordinary Least Squares ◽  
Statistical Correlation ◽  
Least Squares Regression ◽  
Mapping Algorithm ◽  
Spearman’S Rank Correlation

Abstract Objectives To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status. Methods Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE). Results A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859). Conclusions This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.

scholarly journals Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times Per Day

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Shulin Liang ◽  
Chaoqun Wu ◽  
Wenchao Peng ◽  
Jian-Xin Liu ◽  
Hui-Zeng Sun
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Dry Matter ◽  
Prediction Equation ◽  
Dry Matter Intake ◽  
Validation Dataset ◽  
Nutrient Requirements ◽  
Independent Dataset ◽  
Lactating Dairy Cows ◽  
Proposed Model

The objective of this study was to evaluate the feasibility of using the dry matter intake of first 2 h after feeding (DMI-2h), body weight (BW), and milk yield to estimate daily DMI in mid and late lactating dairy cows with fed ration three times per day. Our dataset included 2840 individual observations from 76 cows enrolled in two studies, of which 2259 observations served as development dataset (DDS) from 54 cows and 581 observations acted as the validation dataset (VDS) from 22 cows. The descriptive statistics of these variables were 26.0 ± 2.77 kg/day (mean ± standard deviation) of DMI, 14.9 ± 3.68 kg/day of DMI-2h, 35.0 ± 5.48 kg/day of milk yield, and 636 ± 82.6 kg/day of BW in DDS and 23.2 ± 4.72 kg/day of DMI, 12.6 ± 4.08 kg/day of DMI-2h, 30.4 ± 5.85 kg/day of milk yield, and 597 ± 63.7 kg/day of BW in VDS, respectively. A multiple regression analysis was conducted using the REG procedure of SAS to develop the forecasting models for DMI. The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × BW (kg/day) (R2 = 0.46, mean bias = 0 kg/day, RMSPE = 1.26 kg/day). Moreover, when compared with the prediction equation for DMI in Nutrient Requirements of Dairy Cattle (2001) using the independent dataset (VDS), our proposed model shows higher R2 (0.22 vs. 0.07) and smaller mean bias (−0.10 vs. 1.52 kg/day) and RMSPE (1.77 vs. 2.34 kg/day). Overall, we constructed a feasible forecasting model with better precision and accuracy in predicting daily DMI of dairy cows in mid and late lactation when fed ration three times per day.

Multi-Method Vs Single Method Appraisal of Clinical Quality Indicators for the Emergency Medical Services

2020 ◽  
Author(s):  
Ian Howard ◽  
Peter Cameron ◽  
Maaret Castrén ◽  
Lee Wallis ◽  
Veronica Lindström
Keyword(s):  
Group Discussion ◽  
Rank Correlation ◽  
Healthcare Setting ◽  
Prehospital Emergency Care ◽  
Spearman’S Rank Correlation ◽  
Prehospital Emergency ◽  
Single Method ◽  
Multi Method Approach ◽  
The Individual ◽  
Method Approach

ABSTRACT Background Quality Indicator (QI) appraisal protocols are a novel methodology that combines multiple appraisal methods to comprehensively assess the "appropriateness" of QIs for a particular healthcare setting. However, they remain inadequately explored compared to the single appraisal method approach. This paper aimed to describe and test a QI appraisal protocol versus the single method approach, against a series of QIs potentially relevant to the South African Prehospital Emergency Care setting. Methods An appraisal protocol was developed consisting of two categorical-based appraisal methods, combined with the qualitative analysis of the discussion generated during the consensus application of each method. The output of the protocol was assessed and compared with the application and output of each method. Inter-rater reliability of each particular method was evaluated prior to group consensus rating. Variation in the number of non-valid QIs and the proportion of non-valid QIs identified between each method and the protocol were compared and assessed. Results There was mixed IRR of the individual methods. There was similarly low to moderate correlation of the results obtained between the particular methods (Spearman’s rank correlation=0.42,p&lt;0.001). From a series of 104 QIs, 11 non-valid QIs were identified that were shared between the individual methods. A further 19 non-valid QIs were identified and not shared by each method, highlighting the benefits of a multi-method approach. The outcomes were additionally evident in the group discussion analysis, which in and of itself added further input that would not have otherwise been captured by the individual methods alone. Conclusion The utilization of a multi-method appraisal protocol offers multiple benefits, when compared to the single appraisal approach, and can provide the confidence that the outcomes of the appraisal will ensure a strong foundation on which the QI framework can be successfully implemented.

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