Standard Correlation Research Articles

Distribution and analysis of intraocular pressure and its possible association with glaucoma in children.

To analyze intraocular pressure (IOP) and glaucoma-associated factors in children. A total of 4438 children aged 7-16years (2321 boys and 2117 girls) were included in this study. Various ophthalmologic [IOP, central corneal thickness (CCT), etc.] and demographic (body mass index, etc.) parameters were evaluated. IOP increased between the ages of 7 and 9years, peaking at 9years. IOP increased after reaching a trough at 11years and subsequently stabilized after 14years. Girls exhibited thinner CCT (534.28 ± 30.84µm vs. 537.04 ± 31.33µm, P = 0.003), thicker lens thickness (3.56 ± 0.21mm vs. 3.54 ± 0.20mm, P = 0.001), shorter axial length (22.91 ± 0.93mm vs. 23.32 ± 0.89mm, P < 0.001), shallower anterior chamber depth (2.92 ± 0.27mm vs. 3.00 ± 0.26mm, P < 0.001), higher refraction (- 0.57 ± 1.48 D vs. 0.16 ± 1.35 D, P < 0.001), and higher mean corneal curvature (43.77 ± 1.39 vs. 43.03 ± 1.35, P < 0.001). Multivariable analysis assessed the following IOP-associated factors: thicker CCT [standardized correlation coefficient (SRC) = 0.201, P < 0.001), deeper anterior chamber depth (SRC = 0.059, P = 0.009), shorter axial length (SRC = - 0.086, P = 0.036), lower mean corneal curvature (SRC = - 0.123, P < 0.001), higher refraction (SRC = - 0.090, P < 0.001). IOP fluctuated in children, and a trend toward a higher mean IOP between the ages of 9 and 11years, which stabilized after 14years, was observed. IOP was associated with CCT, anterior chamber depth, axial length, lens thickness, mean corneal curvature, spherical equivalent, and systolic blood pressure.

Potential for body mass index as a tool to estimate body fat in young people

ObjectiveWe aim to determine the anthropometric indicator that is most strongly associated with the percentage of body fat and self-regulation of eating behaviour and physical activity among young university students. MethodsA cross-sectional study was conducted on 3869 Mexican university students, of which 53.9% were women. Standard procedures for anthropometry were followed, including weight, height and waist circumference (WC). This data was used for calculating Body Mass Index (BMI), A Body Shape Index (ABSI), waist-to-height ratio (W/Hr), Body Roundness Index (BRI) and Conicity index (CI). The self-regulation of eating habits scale and the self-regulation of physical activity scale were used. Mean with standard deviation, percentages and Pearson correlation coefficient were estimated. ResultsThe group of men shown a higher prevalence of excess weight compared to the women. Inverse correlations between most anthropometric indices and self-regulation of eating behaviour and physical activity were found. However, in all cases the correlations were weak. The percentage of fat had a medium frequency of association with CI and high with BMI, WC, W/Hr and BRI, where the BMI showed the highest correlation coefficient ConclusionsThe BMI shows the highest magnitude of association with percentage of body fat in university students among the indicators analysed. Therefore it is suggested that nurses use BMI to determine obesity because it is easy to calculate.

Real effective exchange rate and unemployment across post-transition Europe

Purpose: The aim of this paper is to examine the co-movement between the real effective exchange rate and unemployment across post-transition Europe. Methodology: The research data sample in this paper consists of monthly data from 2000M1 to 2019M6 for ten European post-transition countries. After standard correlation analysis, the research followed a wavelet coherence approach, provided time-series analysis in the time-frequency domain and illustrated evolution of the co-movements in the observed period. Results: Conventional approach research results suggest no significant correlation between variables under consideration in cases of Poland and Lithuania. In cases of Latvia and Slovenia, standard correlation coefficients were positive and not in line with the theory. Correlation coefficients supported the theoretical assumption in six other countries included in the study. Wavelet coherence analysis results provided deeper insights into the relationship over time and the frequency domain. Empirical results gained in this research revealed a decline in the unemployment rate accompanied by depreciation of the real effective exchange rate as a prominent pattern at the beginning of the observation period suggesting pro-cyclical monetary policy. Conclusion: During the crisis of 2008 no link between variables under consideration was confirmed, while after the crisis empirical results were in line with the theoretical assumption, suggesting that depreciation of the real effective exchange rate might be used as an instrument to boost employment.

Comparative assessment of conventional periodontal probes and CEJ handpiece of electronic probes in the diagnosis and primary care of periodontal disease.

Objectives:Conventional probes (CPs) have been considered acceptable as diagnostic tools to measure probing pocket depth (PPD) and clinical attachment level (CAL) but are affected by multiple variables. Electronic probes (EPs) provide controlled force, digital readout and data storage in computers. The objectives were to compare the reproducibility in the measurement of PPD and CAL by CP and the newly introduced CEJ handpiece of EP and intra-examiner and inter-examiner errors done in two phases.Methods and Material:Selected 720 periodontal sites in 1st molar of 30 persons with chronic periodontitis ≤4 mm and >4 mm pockets were analysed by two trained investigators in two phases at 2 hours difference by CP and CEJ handpiece of EP. Standard deviation, mean difference, correlation coefficient, P value and student 't' test were done to analyse data.Results:The intra- examiner and inter-examiner analyses revealed that Pearson's correlation coefficient was above 0.080 and 0.722 in the ≤4 mm and >4 mm pockets, respectively. Mean difference was not statistically significant in both groups except in the intra- examiner findings in the 2nd phase. Interprobe analysis depicted a standard error of mean of <0.03 in ≤4 mm pockets, whereas it varied from 0.047–0.056 in >4 mm pockets.Conclusion:In conclusion, EP is advantageous for research purposes by providing automatic recording and long-term maintenance of data storage without the need of an assistant and patient education and motivation, whereas CP appears to be more useful in routine periodontal examination.

МАТЕМАТИЧНІ МЕТОДИ МОДЕЛЮВАННЯ ТА ПРОГНОЗУВАННЯ РИНКУ ПРАЦІ

The labor market is a dynamic system that requires constant monitoring and analysis. To determine the vector of activity of subjects of the labor market and information about market conditions, the need for modeling and forecasting key indicators of the labor market increases. No less important is the methodological collection, analysis and comparison of information related to the functioning of the labor market, forecasting and planning of market activities for further decision-making in management. In modern publications on economics, devoted to the analysis of the labor market, not enough attention is paid to studies that generally cover all methods of economic and mathematical modeling and management of the labor market. Most often, there are scientific works that are related only to control in a specific plane, where one or several methods are applied simultaneously. The publication highlights the main areas of labor market research and methods of economic and mathematical modeling, which are advisable to use in describing the state and dynamics of the sphere of labor relations. The main principles of economic and mathematical modeling in assessing the development of the labor market are highlighted: the consistency of forecasting, the correspondence of forecasting to modern scientific research, the adequacy of forecasts to real processes, the scenario nature of forecasts. The characteristics of economic, mathematical and statistical methods and models that can be used to manage the labor market are given. The paper presents a brief description and the possibility of applying in labor market research such methods as: the system analysis method, aggregate indexing, the indicative method, the comparison method, the assessment of external and internal factors, statistical methods based on the calculation of the standard deviation, variance, correlation coefficients and variations, statistical multivariate analysis, balance models, trend and time series analysis, correlation and regression analysis, simulation modeling, neural networks, sociological research, the method of expert estimates and others. The main software packages for the automation of the above methods are also systematized.

Evaluating implementation strategies for essential newborn care interventions in low- and low middle-income countries: a systematic review.

Neonatal mortality remains a significant health problem in low-income settings. Low-cost essential newborn care (ENC) interventions with proven efficacy and cost-effectiveness exist but have not reached high coverage (≥90%). Little is known about the strategies used to implement these interventions or how they relate to improved coverage. We conducted a systematic review of implementation strategies and implementation outcomes for ENC in low- and low middle-income countries capturing evidence from five medical and global health databases from 1990 to 2018. We included studies of implementation of delayed cord clamping, immediate drying, skin-to-skin contact (SSC) and/or early initiation of breastfeeding implemented in the first hour (facility-based studies) or the 1st day (community-based studies) of life. Implementation strategies and outcomes were categorized according to published frameworks: Expert Recommendations for Implementing Change and Outcomes for Implementation Research. The relationship between implementation strategies and outcomes was evaluated using standardized mean differences and correlation coefficients. Forty-three papers met inclusion criteria. Interventions included community-based care/health promotion and facility-based support and health care provider training. Included studies used 3–31 implementation strategies, though the consistency with which strategies were applied was variable. Conduct educational meetings was the most frequently used strategy. Included studies reported 1–4 implementation outcomes with coverage reported most frequently. Heterogeneity was high and no statistically significant association was found between the number of implementation strategies used and coverage of ENC. This review highlights several challenges in learning from implementation of ENC in low- and low middle-income countries, particularly poor description of interventions and implementation outcomes. We recommend use of UK Medical Research Council guidelines (2015) for process evaluations and checklists for reporting implementation studies. Improved reporting of implementation research in this setting is necessary to learn how to improve service delivery and outcomes and thereby reduce neonatal mortality.

Retrospective comparison of approaches to evaluating inter-observer variability in CT tumour measurements in an academic health centre

BackgroundA growing number of research studies have reported inter-observer variability in sizes of tumours measured from CT scans. It remains unclear whether the conventional statistical measures correctly evaluate the CT...

The Effect of Roasting Temperature on Ferulic Acid Levels of Robusta Coffee Bean with Thin Layer Chromatography (TLC)-Densitometry

The purpose of this study was to quantitatively analyze ferulic acid levels of Robusta coffee bean extractsfrom two samples from different regions (Argopuro and Kaliwining, Jember District), with differentroasting temperatures (180 °C and 200 °C for 10 minutes) using Thin Layer Chromatography (TLC)-Densitometry method. The analytical method used was the TLC-Densitometry, which utilized methanolsolvent p.a; stationary phase: Merck silica Gel 60 F254 plate; chloroform mobile phase: methanol: formicacid (v/v/v) = (85:15:1) in a saturated chromatographic chamber; the test concentration of 50 ppm and theplates were analyzed with the Densitometry winCATS Camag scanner using a UV-Vis detector at 254 nmwavelength and blue fluorescence at 366 nm wavelength. The results showed that the standard correlationcoefficient (R) of ferulic acid was 0.9947. Quantitative analysis of ferulic acid levels obtained on theaverage results of Argupuro coffee bean extract at roasting temperatures 180 °C and 200 °C amounted to1.935598±0.020671 mg/g and 1.419963±0.051633 mg/g, while Robusta Kaliwining coffee bean extract at180°C and 200°C roasting temperature were 3.18087±0.06738 mg/g and 2.420237±0.1989 mg/g. Statisticalanalysis with One-Way Anova obtained p value <0.005. Least Significant Different Test (LSD) obtainedp value <0.005 in each group. Based on the statistical analysis it was concluded that there was an effectof roasting temperature on ferulic acid levels in Robusta coffee bean extract, with the highest ferulic acidcontent obtained in Robusta Kaliwining coffee bean extract in Jember Regency at roasting temperature of180 °C was 3.180875±0.020671 mg/g.

Sustainability-model approach for chloride permeability based on concrete mixture

A predictive chloride permeability model accounting for the concrete mixture and cement hydration is developed. This paper presents the formulation, calibration, evaluation and validation of the proposed model. An experimental program is developed to evaluate the model. Analysis of the results reveal that the model provides a good fit to the experimental data and does not contain outliers or discerning pattern. Furthermore, the model is validated using an extensive database from the literature to test its accuracy and generalization capability. The corresponding standard error and correlation coefficient are 182 Coulombs and 0.90, respectively. Accordingly, the proposed model can be utilized in the design of concrete mixtures to ensure that chloride permeability requirements are met and improve the sustainability of concrete structures.

Contribution from cross-country skiing, start time and shooting components to the overall and isolated biathlon pursuit race performance.

Biathlon is an Olympic sport combining 3-5 laps of cross-country skiing with rifle shooting, alternating between the prone and standing shooting positions between laps. The individual distance and the sprint are extensively examined whereas the pursuit, with start times based on the sprint results, is unexplored. Therefore, the current study aimed to investigate the contribution from start time, cross-country skiing time, penalty time, shooting time and range time to the overall and isolated performance in biathlon World Cup pursuit races. 38 and 37 stepwise linear regression analyses for each of the races were performed, including 112 and 128 unique athletes where 20 and 13 athletes had more than 20 results within top 30 during the seasons 2011/2012-2015/2016 in men and women, respectively. Start time (i.e. sprint race performance) together with penalty time, explained ~80% of the performance-variance (R2) in overall pursuit performance in most races (p<0.01). For isolated pursuit performance, penalty time was the most important component, explaining >54% of the performance-variance in the majority of races, followed by course time (accumulated R2 = .91-.92) and shooting time (accumulated R2 = .98-.99) (p<0.01). Approximately the same rankings of factors were found when comparing standardized coefficients and correlation coefficients of the independent variables included in the regression. Start time (i.e. sprint race performance) is the most important component for overall pursuit performance in biathlon, whereas shooting performance followed by course time are the most important components for the isolated pursuit race performance.

Potential for body mass index as a tool to estimate body fat in young people.

We aim to determine the anthropometric indicator that is most strongly associated with the percentage of body fat and self-regulation of eating behaviour and physical activity among young university students. A cross-sectional study was conducted on 3,869 Mexican university students, of which 53.9% were women. Standard procedures for anthropometry were followed, including weight, height and waist circumference. This data was used for calculating Body Mass Index (BMI), A Body Shape Index, waist-to-height ratio, Body Roundness Index and Conicity index. The self-regulation of eating habits scale and the self-regulation of physical activity scale were used. Mean with standard deviation, percentages and Pearson correlation coefficient were estimated. The group of men shown a higher prevalence of excess weight compared to the women. Inverse correlations between most anthropometric indices and self-regulation of eating behaviour and physical activity were found. However, in all cases the correlations were weak. The percentage of fat had a medium frequency of association with Conicity index and high with BMI, waist circumference, waist-to-height ratio and Body Roundness Index, where the BMI showed the highest correlation coefficient CONCLUSIONS: The BMI shows the highest magnitude of association with percentage of body fat in university students among the indicators analysed. Therefore it is suggested that nurses use BMI to determine obesity because it is easy to calculate.

Types of Statistical Indicators Characterized by 2-Pre-Hilbert Spaces

In this article, we established new results related to a 2-pre-Hilbert space. Among these results we will mention the Cauchy-Schwarz inequality. We show several applications related to some statistical indicators as average, variance and standard deviation and correlation coefficient, using the standard 2-inner product and some of its properties. We also present a brief characterization of a linear regression model for the random variables in discrete case.

Comparison of Ten Potential Evapotranspiration Models and Their Attribution Analyses for Ten Chinese Drainage Basins

Potential evapotranspiration (EPET) is usually calculated by empirical methods from surface meteorological variables, such as temperature, radiation and wind speed. The in-situ measured pan evaporation (ETpan) can also be used as a proxy for EPET. In this study, EPET values computed from ten models are compared with observed ETpan data in ten Chinese river basins for the period 1961−2013. The daily observed meteorological variables at 2267 stations are used as the input to those models, and a ranking scheme is applied to rank the statistical quantities (ratio of standard deviations, correlation coefficient, and ratio of trends) between ETpan and modeled EPET in different river basins. There are large deviations between the modeled EPET and the ETpan in both the magnitude and the annual trend at most stations. In eight of the basins (except for Southeast and Southwest China), ETpan shows decreasing trends with magnitudes ranging between −0.01 mm d−1 yr−1 and −0.03 mm d−1 yr−1, while the decreasing trends in modeled EPET are less than −0.01 mm d−1 yr−1. Inter comparisons among different models in different river basins suggest that PETHam1 is the best model in the Pearl River basin, PETHam2 outperforms other models in the Huaihe River, Yangtze River and Yellow River basins, and PETFAO is the best model for the remaining basins. Sensitivity analyses reveal that wind speed and sunshine duration are two important factors for decreasing EPET in most basins except in Southeast and Southwest China. The increasing EPET trend in Southeast China is mainly attributed to the reduced relative humidity.

Analysis of groundwater level variability in the middle mountain area of Pyoseon watershed in Jeju Island using normalized standard deviation and cross correlation coefficient

Analysis of groundwater level variability in the middle mountain area of Pyoseon watershed in Jeju Island using normalized standard deviation and cross correlation coefficient

Differential Continuous Wave Photoacoustic Spectroscopy for Non-Invasive Glucose Monitoring

In vivo and in vitro studies of differential continuous wave photoacoustic spectroscopy (DCW-PAS) for non-invasive blood glucose monitoring were performed. The DCW-PAS technique utilizes amplitude modulation of dual wavelengths of light to determine changes in glucose concentration. The study compared DCW-PAS measurements with results from invasive blood glucose sensor measurements during oral glucose tolerance tests (OGTTs) of healthy people. The trends in blood glucose levels (BGLs) obtained from invasive sensors and from the photoacoustic signal have good agreement, with the standard error and correlation coefficient against BGLs of 48 mg/dL or less and 0.80, respectively. Our proposed photoacoustic spectroscopy (PAS) method shows high potential for use in a non-invasive BGL sensor.

Microstructure Model for Predicting the Sorptivity of Concrete Mixtures

Durability of concrete structures is determined by the mass transport properties of concrete. The performance of concrete exposed to aggressive environments is a function mainly of the penetrability of the pore structure i.e. the rate of absorption (sorptivity) due to capillary rise. This study involves the development of a predictive sorptivity microstructure model accounting for the type of cement, cement degree of hydration, mixtures proportion, aggregates gradation and packing density, and air content. This paper presents the formulation and validation of a sorptivity model. An experimental program is designed to evaluate the proposed model. Evaluation of the proposed model revealed that the model is a good fit to the experimental data and does not contain outliers or discerning pattern. The corresponding standard error and correlation coefficient are 0.00039 mm/s1/2 and 0.89, respectively. Results of statistical evaluation revealed that the proposed model is significant in its prediction of the outcome, where the p-value was found to be less than 0.001. The proposed predictive sorptivity model can be employed in the design of concrete mixtures to meet specific durability requirements as a priority and ensure quality control. Furthermore, the proposed model can be utilized to improve the durability prediction of concrete mixtures.

Mapping seafloor topography of gulf of Guinea using an adaptive meshed gravity-geologic method

An adaptive mesh form of the gravity-geologic method, known as improved Gravity-Geologic Method (iGGM), was implemented on free-air gravity anomalies and shipborne depths to obtain an improved 1′ × 1′ bathymetry model of the Gulf of Guinea (15°W–5°E, 4°S–4°N). An optimal density contrast of 8000 kg/m3 was used for the whole area. The iGGM model compared well with NGDC, ETOPO1, and SIO models; with difference standard deviations and correlation coefficients being 180.20 m, 0.9248, 184.34 m, 0.9551, and 179.84 m, 0.8886, respectively. These prove generally that iGGM is efficient for estimating bathymetry with limited shipborne depths. The influence of shipborne depths quantity and optimal density contrast on bathymetry inversion are analysed, respectively, for the whole region and three subregions (15°W–8°W, 4°S–2°N; 7°W–2°E, 2°S–2°N; and 1°E–5°E, 4°S–0°N). Results showed that, compared with the mountainous areas, higher inversion accuracy (standard deviation of test differences less than 50 m) is achievable in the low-lying region using fewer shipborne depths. With 75% of shipborne depths used for the entire model, the standard deviation of differences between iGGM and shipborne depths at test points was 184.74 m. This indicates that to further improve the region’s bathymetry, more ship sounding is required in the mountainous areas. Numerical results showed different optimal densities should be selected for different areas, especially for the mountainous areas. Using a common density contrast in the whole region may limit the accuracy of the bathymetry inversion.

Microseismic Signal Denoising via Empirical Mode Decomposition, Compressed Sensing, and Soft-thresholding

Microseismic signal denoising is of great significance for P wave, S wave first arrival picking, source localization, and focal mechanism inversion. Therefore, an Empirical Mode Decomposition (EMD), Compressed Sensing (CS), and Soft-thresholding (ST) combined EMD_CS_ST denoising method is proposed. First, through EMD decomposition of the noise signal, a series of Intrinsic Mode Functions (IMF) from high frequency to low frequency are obtained. By calculating the correlation coefficient between each IMF and the original signal, the boundary component between the signal and the noise was identified, and the boundary component and its previous components were sparsely processed in the discrete wavelet transform domain to obtain the original sparse coefficient θ. Second, θ is filtered by ST to get the reconstruction coefficient θnew after denoising. Then, CS was used to recover and reconstruct θnew to get the denoised IMFnew component and then recombined with the remaining IMF components to get the signal after denoising. In the simulation experiment, the denoising process of EMD_CS_ST method is introduced in detail, and the denoising ability of EMD_CS_ST, DWT, EEMD, and VMD_DWT under 10 different noise levels is discussed. The signal-to-noise ratio, signal standard deviation, correlation coefficient, waveform diagram, and spectrogram before and after denoising are compared and analyzed. Moreover, the signals obtained from the underground cavern of the Shuangjiangkou hydropower station were denoised by the EMD_CS_ST method, and the signals before and after denoising were analyzed by time-frequency spectrum. These results show that the proposed method has better denoising ability.

Characterization of the hydro-geological regime of Yangtze River basin using remotely-sensed and modeled products

The hydrology of the Third Pole, Asia's freshwater tower, has shown considerable sensitivity to the impacts of climate change and human interventions, which affect the headwaters of many rivers that originate therein. For example, the Yangtze River has its basin (YRB) experiencing wetness of terrestrial water storage (TWS), whose rainfall seems to be the primary source as inferred from the previous studies. Consequently, it is crucial to understand the contributions of each TWS's sub-domain - i.e., groundwater (GWS); total water content (TWC) stored as soil moisture, ice/snow, and canopy; and the surface water (SWS) storages - on YRB's wetness. Hence, SWS, from altimetry and imagery satellites, and TWC, from Global Land Data Assimilation System, are inverted considering the same basis function as for TWS from the Gravity Recovery and Climate Experiment, which account for the differences in the resolutions inherent in each product. Furthermore, a “tie-in” signal approach is used to fit the temporal patterns of GWS, TWC, and SWS to TWS (i.e., the observations). Results show improvements in the reconstructed GWS series concerning standard deviation, correlation coefficient, and Nash–Sutcliffe efficiency of 22%, 27%, and 120%, respectively, regarding the use of the TWS-budget equation. The reconstructed time series of GWS, TWC, and SWS present an increase of 1.76, 2.69, and 0.14 mm per year (mm/yr) and that YRB loses water stored at its aquifers 55% of the time (regarding 2003–2016 period) based on the quantile function of storage (QFS). The QFS's slope shows that TWS has a fast and small storage potential w.r.t. GWS since inland waters and soil moisture reflect the dryness impacting TWS first. Despite the evidence of an increase of 19.05 mm/yr in annual precipitation, which seems to explain the bulk in TWS, further investigation to characterize controls on TWS memory within YRB is still necessary.

Color Restoration for Full-Waveform Multispectral LiDAR Data

The current full-waveform data at a single wavelength can mainly retrieve the geometric attributes of targets along the light path by detecting waveform components, resulting in the lack of spectral or color attribute information. This kind of device relies on a digital camera for acquiring the color information, however, which is inevitably limited by the lighting conditions and geometric registration errors. With the development of multispectral light detection and ranging (LiDAR) or even hyperspectral LiDAR that often utilize a supercontinuum laser source covering the whole visible light band, including red, green and blue bands, the simultaneous acquisition of color and spatial information becomes possible and makes passive imaging data no longer necessary. In this study, we propose a color restoration method for a full-waveform multispectral LiDAR (FWMSL) system. Additionally, we develop a multispectral lognormal function to fit the tailing echoes measured by FWMSL further accurately. Experimental data from our FWMSL system are used to evaluate the performance of the proposed method. The relative standard deviation, correlation coefficient (R2) and color difference ( Δ E ) metrics suggest that the color restoration for the full-waveform multispectral data is feasible.