Calculation Of Correlation Coefficient Research Articles

Implementation of Child Friendly Pesantren Program

This research discusses the correlation between the results of socialization of child-friendly pesantren program by the ministry of religion and the ministry of women's empowerment and protection on the program implementation in pesantrens in Padangpanjg City, West Sumatra. The purpose of the research was to obtain information about the correlation between the results of socialization on the implementation of the child-friendly pesantren program. The hypothesis in this study is that there is a correlation between the results of socialization and the on the implementation of child-friendly pesantren programs in Pesantrens in Padangpanjang City. The research method is descriptive method.The technique used in this research is proportionate stratified random sampling technique.The results showed that the proposed hypothesis was accepted that there was a significant correlation between the results of socialization on the implementation of the child-friendly pesantren program with he correlation coefficient calculation known that r hitung is 0,660 wheres r table with significant degree 5% for N = 62 and df = N-2 = 62 - 2 = 60 is 0,254. Thereby r hitung ≥ rtabel or 0,660 > 0,254, thereby Ha is accepted.

The Opposite Behaviors of Proton and Electron Temperatures in Relation to Solar Wind Magnetic Energy: Parker Solar Probe Observations

Solar wind heating is an outstanding issue that has been discussed for decades. Research on the connection between solar wind particle temperatures and turbulence may provide insight into this issue. Based on Parker Solar Probe observations, this paper investigates the properties of solar wind proton and electron temperatures in relation to turbulent magnetic energy, via the calculation of correlation coefficients (CCs) between particle temperatures and magnetic energy. The calculations are regulated by the spatial scale, plasma beta (β), and the angle between the solar wind velocity and background magnetic field, where the plasma beta is the ratio of plasma thermal to magnetic pressure. Results show that the correlation between proton temperature and magnetic energy is positive and can be strong with a CC exceeding 0.8. The strong correlation preferentially occurs at ion scales, with the wind velocity and background magnetic field quasi-perpendicular and over a wide beta range (β < 3.0). On the other hand, the correlation between electron temperature and magnetic energy is commonly negative, often with an intermediate or negligible CC, accordingly. The CC with an amplitude up to 0.8 can arise at larger scales with the wind velocity and background magnetic field quasi-(anti)parallel and in the low-beta case (β < 0.6). The implication of these findings on the physics of turbulent heating in the solar wind is discussed.

The texture analysis of computed tomography studies in clear cell renal cell carcinoma: reproducibility of 2D and 3D segmentation

Background: Differentiation of tumor grade at the preoperative stage is of utmost importance for the modification of the treatment strategy and the extent of operation. However, the routine analysis of computed tomography (CT) data in clear cell renal cell carcinoma (ccRCC) does not allow for reliable determination of the tumor grade.&#x0D; Aim: To assess the reproducibility of the results of 2D and 3D segmentation of a kidney tumor in the cortico-medullary and nephrographic phases of CT studies, as well as the reproducibility of the first order texture parameters for 2D and 3D tumor segmentation in patients with verified ccRCC.&#x0D; Materials and methods: This retrospective study included the CT data of 50 patients with morphologically verified ccRCC obtained before their surgical treatment. The first patient group included the patients with the renal tumor size in the axial plane of ≥ 4 cm (28 patients, 29 CT studies), and the second patient group included those with the renal tumor size in axial plane of 4 cm (22 patients, 23 CT studies). Two radiologists independently performed segmentation of the renal tumor in the cortico-medullary and nephrographic phases of CT procedures done under a standard protocol with the bolus intravenous contrast enhancement. A two-dimensional region of interest (2D ROI) was selected by the investigators on a subjectively selected axial slice, where the tumor had the largest size. When forming a three-dimensional region of interest (3D ROI), the entire tumor volume was segmented. Next, the statistical analysis of the segmentation results and the results of calculation of the first order texture indices was performed with calculation of the intra-class correlation coefficient (ICC) to assess the strength of the data correlation. The ICC of ≥ 0.75 demonstrated the reproducibility of the segmentation results and the first order texture indices.&#x0D; Results: The 3D segmentation method for ccRCC demonstrated the best ROI reproducibility results, regardless of the tumor size and the phase of contrast enhancement, with the ICC values of 0.961 (95% confidence interval: 0.946–0.971) for the cortico-medullary phase and 0.969 (95% CI: 0.958–0.977) for the nephrographic phase. The 2D tumor segmentation method showed unsatisfactory ROI reproducibility, with the ICC values of ≤ 0.058; however, the unsatisfactory reproducibility of the segmentation results in the patients with ccRCC tumor size of ≥ 4 cm did not significantly affect the reproducibility of the Entropy and Energy texture indices (good to excellent correlation). With the 3D segmentation of ccRCC, most first-order texture metrics were reproducible, with the exception of the Kurtosis parameter. The Entropy and Energy scores in both patient groups demonstrated a high degree of reproducibility. In the 2D tumor segmentation, high reproducibility of the first order texture metrics was obtained for the Entropy and Energy indices.&#x0D; Conclusion: The 3D segmentation of the CT data for ccRCC has high reproducibility, the most first-order textural features were excellently reproducible when segmentations were performed in 3D. The 2D CT data segmentation method for ccRCC demonstrated low reproducibility; however, some of the first order texture indices were reproducible. Both segmentation methods can be used for the texture analysis of CT images.

Decreased Posterior Tibial Slope and Its Association With Pediatric Posterior Cruciate Ligament Injury

Background: Recent adult studies have demonstrated that decreased posterior tibial slope angle (PTSA) may be a risk factor for posterior cruciate ligament (PCL) injury. However, there is no study investigating this phenomenon in a pediatric population. Understanding risk factors for PCL injuries among a pediatric population is important given the recent rise in athletic competition/specialization and sports-related injuries. Hypothesis/Purpose: The purpose of this study was to compare PTSA between pediatric patients sustaining a primary PCL tear compared with age- and sex-matched controls. It was hypothesized that pediatric patients sustaining a PCL tear would have a decreased PTSA compared with controls, with decreased PTSA being associated with higher odds of PCL injury. Study Design: Cohort study; Level of evidence, 3. Methods: The records of all patients sustaining a PCL injury between 2006 and 2021 at a level 1 pediatric trauma center were reviewed. Patients aged ≤18 years with magnetic resonance imaging–confirmed PCL tear were included. Excluded were patients with concomitant anterior cruciate ligament tears, previous PCL reconstruction, or previous coronal plane realignment. A control cohort, with their ligament shown as intact on magnetic resonance imaging scans, was matched based on age and sex. PTSA was measured on lateral radiographs of the injured knee or tibia. The mean PTSA was compared between cohorts, and odds ratios were calculated based on the normal slope range (7°-10°) described in the literature, an upper range (>10°), and a lower range (<7°). Inter- and intrarater reliability were determined via calculation of an intraclass correlation coefficient. Results: Of the 98 patients who sustained a PCL injury in this study period, 59 (60%) met inclusion criteria, and 59 healthy knee controls were matched. There were no differences between the cohorts for age (P = .90), sex (P > .99), or body mass index (P = .74). The PCL cohort had a lower mean ± SD PTSA compared with the control group (5.9°± 2.7° vs 7.3°± 4.3°; P = .03). PTSA <7° was associated with a 2.8 (95% CI, 1.3-6.0; P = .01) times risk of PCL tear. Conversely, PTSA >10° was associated with a 0.27 (95% CI, 0.09-0.81; P = .02) times risk of PCL tear. These PTSA measurements demonstrated acceptable intrarater and interrater reliability. Conclusion: PTSA <7° was associated with an increased odds of PCL injury, whereas a slope >10° was associated with a decreased odds of PCL injury in a pediatric population. These findings corroborate similar outcomes in adult studies; however, further studies are needed to elucidate PTSA as a risk factor for PCL injury.

Социально-экономическое благополучие как условие формирования потенциального человеческого капитала

The materials of the article are a continuation of a series of the authors’ research devoted to the study of correlation relationship closeness between the level of socio-economic development of the countries and the development of national human capital. Quantitative relationship between the level of socio-economic well-being of the country and development potential of future human capital is the object of attention in the article. Based on the author's interpretation of the concept of "potential human capital" from the standpoint of correlation and regression analysis, influence of socio-economic well-being parameters on the current opportunities of formation and realization of human capital of future generations is considered. Within the framework of the methodological tools of regression analysis, based on calculations of correlation coefficients, there was an attempt to quantify the degree of influence on the dependent variable (potential human capital) of various parameters of socio-economic well–being of countries – per capita income, non-cost characteristics of social development (competitiveness of national economy, level of social progress, level of prosperity, and level of happiness).

Influence on Sample Determination for Deep Learning Electromagnetic Tomography.

Deep learning (DL) has been frequently applied in the image reconstruction of electromagnetic tomography (EMT) in recent years. It offers the potential to achieve higher-quality image reconstruction. Among these, research on samples is relatively scarce. Samples are the cornerstone for both large and small models, which is easy to ignore. In this paper, a deep learning electromagnetic tomography (DL-EMT) model with nine elements is established. Complete simulation and experimental samples are obtained based on this model. On the sample sets, the reconstruction quality is observed by adjusting the size and configuration of the training set. The Mann-Whitney U test shows that beyond a certain point, the addition of more samples to the training data fed into the deep learning network does not result in an obvious improvement statistically in the quality of the reconstructed images. This paper proposes a CC-building method for optimizing a sample set. This method is based on the Pearson correlation coefficient calculation, aiming to establish a more effective sample base for DL-EMT image reconstruction. The statistical analysis shows that the CC-building method can significantly improve the image reconstruction effect in a small and moderate sample size. This method is also validated by experiments.

IJCM_152A: Assessment of Supportive Care Needs of Breast Cancer Patients and their Caregivers - A Cross Sectional Study at a Tertiary Care Centre, Vadodara

Background: Cancer diagnosis can be difficult for the patients as well as their families; who bear a disproportionate amount of caring burden. Research indicates that as patients’ needs rise, so do those of their caregivers. For holistic health care delivery, it is important for service providers to be cognizant of the difficulties faced by both. Objective: 1. To assess the needs of breast cancer patients and their caregivers. 2. To explore the factors associated with needs of the patients and their caregivers 3. To assess the relation between the needs of the patients and their caregivers Methodology: One hundred and fifty dyads of patients and their caregivers were purposely sampled and administered Supportive-Care-Needs-Surveys (SCNS) Short-form34 (SF-34), and SCNS-Partners and Caregivers respectively, by the interviewer in local language. Cronbach a was used to check reliability and median (IQR) scores were calculated for domains in each survey. Univariate analysis was done to identify factors affecting needs, followed by calculation of correlation coefficient between the needs of patients and of their caregivers. Results: All domains in the two scales were acceptable (Cronbacha&gt;0.6) except Patient Care and Support (0.51) and Sexuality (0.19) domains in SCNS-SF34. Highest needs were reported by patients in Physical and Daily Living domain 40.62(31.5-56.5) and by caregivers in Work and Social Security 30.4(25-35.7), and Emotional and Psychological Needs 30.4(21.4- 35.7) domains. Patients’ and caregivers’ needs were significantly associated with patient’s disease status (p&lt; 0.05), and a moderately positive correlation (r (148) = 0.41, p&lt;0.001) was found between their needs. Conclusion: Patients and caregivers both reported unmet needs which were influenced by the patient’s disease status, and caretakers’ needs increased in tandem with patients’ needs. Studies to validate existing scales or create new ones and larger-scale comparable research including the private sector could aid in generalizability.

Data-mining framework for in-depth quantitative study of influences on low-wind-velocity area from morphological parameters of cuboid-form buildings

Wind environment is important in architectural sustainable design, as existing studies show that it can be considerably influenced by building morphologies. This study aimed to develop a data-mining framework to quantitatively evaluate and compare influences on Low-Wind-Velocity Area (LWVA) of common cuboid-form buildings with typical morphological parameters. The data-mining framework was originally developed by integrating multiple computational methods for rapid in-depth iterative analyses, including the generation of building models using parametric modelling, the big data generation based on hybrid model, and the statistical metric analysis method. The hybrid model was created by combining the CFD model and machine learning model. The accuracy and efficiency of the framework were fully demonstrated through the comprehensive validation and analyses of different models. The data of more than fifty thousand building cases with different morphological parameters and relevant wind conditions were generated and analyzed. Influences on LWVA of morphological parameters of cuboid-form building was comprehensively evaluated, including the visualization of multiple parameters, calculation and comparison of several correlation coefficients. It suggested that the reduction of height and width on the windward side would significantly decrease the LWVA and promote the outdoor ventilation. The change of depth would have relatively limited influence on the LWVA. Multivariate regression model-fit and variance analyses were further implemented, and it was found that there was a relatively significant linear correlation between the LWVA and morphological parameters. The equation of multivariate regression model was provided for extra rapid prediction. The study outcome could contribute to efficient evaluation of LWVA and provide useful information for sustainable design.

Development and Validation of the Bilingual Catalan/Spanish Cross-Cultural Adaptation of the Consensus Auditory-Perceptual Evaluation of Voice.

This study aimed to develop a valid and reliable bilingual version of the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V) for the auditory-perceptual evaluation of voice in Catalan and Spanish speakers. The development of this CAPE-V adaptation included Delphi methodology with 20 voice and speech experts reaching consensus on the optimal adapted terminology of the perceptual vocal attributes, considering also input from the original instrument authors. The adaptation and validation of vocal tasks followed a sequential validation procedure, with input from phoneticians and speech-language pathologists. Following pilot testing with a large sample of speech-language pathology students, a refined adapted version was empirically tested for validity and reliability. Concurrent validity was assessed by comparing the adapted CAPE-V with the reference Grade, Roughness, Breathiness, Asthenia, Strain scale. Construct validity was assessed through convergent and discriminant validity analysis. Intrarater and interrater reliability were assessed via intraclass correlation coefficient calculations. User experience was evaluated through a questionnaire. Scale properties were validated using a confusion matrix, and cutoff values were calculated to achieve the optimal balance between sensitivity and specificity. Through a formalized consensus process, optimal Catalan/Spanish terminology was determined for the perceptual attributes of voice present in the CAPE-V. An adapted protocol of tasks was obtained that preserves the objectives of the original instrument and the relevance of the phonetic criteria in the target languages. The results demonstrated concurrent validity, construct validity, and intrarater reliability. Interrater reliability was found to depend on the extent to which evaluators shared their internal standards. The raters identified CAPE-V as an effective and preferred instrument. An adapted, validated version of the CAPE-V is made available to clinical professionals for the evaluation of voice in Catalan and Spanish speakers.

Study on the Relationship between Hotspots and Air Pollution Standard Index Based on Carbon Monoxide Concentration in West Kalimantan

Hotspots, indicating active fires and potential sources of air pollution, are a major concern due to their impact on air quality in West Kalimantan. In this study, an analysis was carried out regarding the relationship of hotspots to the Air Pollution Standard Index (ISPU) based on the carbon monoxide (CO) parameter. This study aimed to determine the relationship between forest fires and air pollution levels. The data used in this study is in the form of monthly average CO concentration data and coordinates of hotspots in 2017-2021. To determine the effect of CO concentration, CO concentration was converted into ISPU and then mapped using the Inverse Distance Weighting (IDW) interpolation method. In addition, the overlay technique is also applied to the map and the correlation coefficient calculation between ISPU data and hotspot data. The study results show that the annual average number of hotspots ranges from 769 to 3,612, while the average ISPU ranges from 22.21 to 59.03. The highest average number of hotspots occurred in 2019, with 3,612 hotspots and the highest average ISPU value of 59.03, categorized as moderate. However, when examined monthly, the highest average number of hotspots is observed in August and September, with 8,505 and 8,321 hotspots, respectively, and average ISPU values of 55.36 and 88.32, categorized as moderate. Furthermore, the correlation coefficient between the average number of hotspots and the average ISPU per month is 0.91, and per year is 0.98, indicating a very high relationship. Spatially, clustered hotspot locations correspond to higher ISPU values. This implies that as the number of hotspots increases, the ISPU value based on CO concentration increases.

On the pixel selection criterion for the calculation of the Pearson's correlation coefficient in fluorescence microscopy.

Colocalisation microscopy analysis provides an intuitive and straightforward way of determining if two biomolecules occupy the same diffraction-limited volume. A popular colocalisation coefficient, the Pearson's correlation coefficient (PCC), can be calculated using different pixel selection criteria: PCCALL includes all image pixels, PCCOR only pixels exceeding the intensity thresholds for either one of the detection channels, and PCCAND only pixels exceeding the intensity thresholds for both detection channels. Our results show that PCCALL depends on the foreground to background ratio, producing values influenced by factors unrelated to biomolecular association. PCCAND focuses on areas with the highest intensities in both channels, which allows it to detect low levels of colocalisation, but makes it inappropriate for evaluating spatial cooccurrence between the signals. PCCOR produces values influenced both by signal proportionality and spatial cooccurrence but can sometimes overemphasise the lack of the latter. Overall, PCCAND excels at detecting low levels of colocalisation, PCCOR provides a balanced quantification of signal proportionality and spatial coincidence, and PCCALL risks misinterpretation yet avoids segmentation challenges. Awareness of their distinct properties should inform their appropriate application with the aim of accurately representing the underlying biology.

Machine learning integration of multi-modal analytical data for distinguishing abnormal botanical drugs and its application in Guhong injection

BackgroundDetermination of batch-to-batch consistency of botanical drugs (BDs) has long been the bottleneck in quality evaluation primarily due to the chemical diversity inherent in BDs. This diversity presents an obstacle to achieving comprehensive standardization for BDs. Basically, a single detection mode likely leads to substandard analysis results as different classes of structures always possess distinct physicochemical properties. Whereas representing a workaround for multi-target standardization using multi-modal data, data processing for information from diverse sources is of great importance for the accuracy of classification.MethodsIn this research, multi-modal data of 78 batches of Guhong injections (GHIs) consisting of 52 normal and 26 abnormal samples were acquired by employing HPLC-UV, -ELSD, and quantitative 1H NMR (q1HNMR), of which data obtained was then individually used for Pearson correlation coefficient (PCC) calculation and partial least square-discriminant analysis (PLS-DA). Then, a mid-level data fusion method with data containing qualitative and quantitative information to establish a support vector machine (SVM) model for evaluating the batch-to-batch consistency of GHIs.ResultsThe resulting outcomes showed that datasets from one detection mode (e.g., data from UV detectors only) are inadequate for accurately assessing the product's quality. The mid-level data fusion strategy for the quality evaluation enabled the classification of normal and abnormal batches of GHIs at 100% accuracy.ConclusionsA quality assessment strategy was successfully developed by leveraging a mid-level data fusion method for the batch-to-batch consistency evaluation of GHIs. This study highlights the promising utility of data from different detection modes for the quality evaluation of BDs. It also reminds manufacturers and researchers about the advantages of involving data fusion to handle multi-modal data. Especially when done jointly, this strategy can significantly increase the accuracy of product classification and serve as a capable tool for studies of other BDs.

INLINE DYNAMOMETRY PROVIDES RELIABLE MEASUREMENTS OF QUADRICEPS STRENGTH IN HEALTHY AND ACL-RECONSTRUCTED INDIVIDUALS AND IS A VALID SUBSTITUTE FOR ISOMETRIC ELECTROMECHANICAL DYNAMOMETRY FOLLOWING ACL RECONSTRUCTION

BackgroundQuadriceps strength testing is recommended to guide rehabilitation and mitigate the risk of second injury following anterior cruciate ligament (ACL) reconstruction. Hand-held dynamometry is a practical alternative to electromechanical dynamometry but demonstrates insufficient reliability and criterion validity in healthy and ACL-reconstructed participants respectively. The purpose of this study is to investigate the reliability and concurrent validity of inline dynamometry for measuring quadriceps strength. The hypotheses are that intra-class correlation coefficient (ICC) values will be >0.90 for reliability and concurrent validity. MethodsThis was a cross sectional study using a within-participant, repeated measures design. Isometric quadriceps testing was performed at 60° knee flexion in 50 healthy and 52 ACL-reconstructed participants. Interrater reliability, intrarater reliability, and concurrent validity of inline dynamometry was investigated through calculation of intra-class correlation coefficients (ICCs), Bland-Altman analysis, linear regression, standard error of measurement (SEM) and minimal detectable change (MDC). ResultsThe lower bounds of the 95% confidence intervals were >0.90 for all reliability and validity ICCs in healthy and ACL-reconstructed participants, except for intrarater reliability in healthy participants using absolute scores (ICC = 0.936 [95% CI 0.890-0.963]). In ACL-reconstructed participants, Bland-Altman bias was 0.01 Nm/kg for absolute and average scores, limits of agreement were -11.74% to 12.59% for absolute scores, the SEM was 0.13Nm/kg (95% CI 0.10 - 0.17) and the MDC was 0.36Nm/kg (95% CI 0.28 – 0.47). ConclusionInline dynamometry is a reliable and economical alternative to electromechanical dynamometry for the assessment of quadriceps strength following ACL-reconstruction.Clinical trial registration number: ClinicalTrials.gov (NCT05109871)

The measurement and analysis of similarity degree on data from two types of seismic recorders

Seismic instruments are widely used in projects related to geophysical prospecting. Quality data from seismic recorders help to determine subterranean structures with high precision. This paper first introduces a field experiment carried out by deploying seismic stations equipped with two kinds of seismic recorders: GEI (China) and Reftek 130 (USA). Then, the three-component seismograms from GEI are measured and evaluated by comparing with those from Reftek 130 in different aspects: waveforms in time and frequency domain, quantitative analysis by calculation and statistic of correlation coefficient, and signal to noise ratio of seismic signal. Our results were presented by multiple images as the following: (I) Both the time and frequency waveforms of GEI were almost exactly coincident with those of Reftek 130, with over 98.60 percent of the correlation coefficients in the time domain within 0.95–1.0, and all those in the frequency domain above 0.9977. (II) The accurate time lag estimation of GEI’s signal was gained by the lag and correlation algorithms based on left–right sliding windows. The GEI clock was 7.3545 ns behind the Reftek 130 clock after every 1 s, which could be utilized to correct the internal clock to improve the synchronous accuracy of seismic recorders. (III) Some seismic signals from GEI were obviously stronger than those from Reftek 130. Our results may potentially promote and support the optimization of seismic recorders and their application in geophysics methods.

Validation of precipitation obtained from GPM and H-SAF satellite data with relation to Ukrainian ground weather stations' data

The main objective of this study is to validate H-SAF and GPM satellite precipitation data for the territory of Ukraine. Validation was carried out by comparing satellite data with data from ground weather stations of Ukrainian Hydrometeorological Center and included the following stages: data collection and processing, bringing the data to the same spatial and temporal resolution, calculation of correlation coefficients and construction of confusion matrices. Correlation coefficients were calculated for each of the stations for two studied periods (the first period - April-September 2020, the second period - April-September 2021). In addition, to ensure a more detailed analysis, confusion matrices were constructed based on division of precipitation into classes of different intensity. The comparative analysis showed that a larger number of stations (117) has a correlation coefficient of 0.5 - 0.8 with relation to GPM data, and, as for HSAF precipitation data, a larger number of stations (59) has a low correlation coefficient (0 - 0.3). Confusion matrices were calculated for the following four classes of rainfalls (mm): “0-2”, “2-5”, “5-10”, “&gt;10”. The confusion matrices coefficients showed that low-intensity precipitation or “no precipitation”, as well as high-intensity precipitation, can be determined by a satellite with high accuracy as opposed to the ground-based weather station measurements. Thus, according to the "specificity" indicator, a precipitation class &gt;10 mm has the highest level of correspondence of satellite data (H-SAF, GPM Late, GPM Early) to ground data. The low value of the "specificity" for the range of 0-2 mm is explained by the fact that satellite methods are able to detect very low values of precipitation intensity, while the station shows their absence – 0 mm. Thus, according to the values of the confusion matrices, we see that a large part of the values of ground measurements of precipitation in the range of 0-2 mm are shown by the satellite method as “2-5 mm” class. We can also see that the “2-5 mm” class by satellite has the most confusion with the 0-2 mm class by station (for H-SAF, GPM Late, GPM Early). But based on the high values of the "recall" for the range of 0-2 mm (for H-SAF, GPM Late, GPM Early), we can conclude that when the station does not show this amount of precipitation (0-2 mm), then the satellite also shows another class of values. The values of "precision" coefficient show that the satellite measurements are actually reliable. This means that presence or absence of precipitation may be determined precisely, since the highest value of the "precision" coefficient is typical for low and high amounts of precipitation (on average 0.76 and 0.66, respectively). Detected by satellites, heavy precipitation or no precipitation are also confirmed in most cases by ground stations. Based on the results of the validation, GPM and H-SAF satellite precipitation data products can be used for rainfall monitoring and considered as an additional source of meteorological information.

Contaminants Correlation and Curtailment Prospect of Waterhyacinth, Waterlettuce and Vetiver Grass in Wastewater Treatment.

This study seeks to elaborate the correlation of physicochemical parameters and heavy metals from a wastewater effluent in Zaria. The contaminants reduction capacity of Vetiver grass (C. zizanoides), water hyacinth (E. crassipes) and Water lettuce (P.stratiotes) were analysed.Temperature, pH, EC, TDS, Cl, PO4-, DO, BOD, COD, Na, K, NO3, TSS, NH3, SO4 and Cu, Cd, Pb, Mn, Mg, Co, Ni, Cr and Zn concentrations were determined using standard method,digestion and assessment of heavy metals using atomic absorption spectrophotometry machine. There was positive correlation between TDS with EC, BOD with NO3-N, pH with Temperature, DO with COD and N, and Cl with K. Zn with Pb and Cd, Cr with Co indicating common source of contamination. Negative correlation was observed between HCO3 with NH3.N and SO4-, Temperature with N and DO, K with BOD and NO3-N, Cr with Ni, Mg with Cu and Zn indicating uncommon source of contamination. The significant correlation was verified by using t-test. The systematic calculation of correlation coefficient between water quality parameters and between heavy metals was carried out. Hydroponic method of phytoremediation was adopted to evaluate the curtailment potentials of the three plants.There was significant difference at P ≤ 0.05 (95% confidence) across days 7, 14 and 21 in reduction during treatment with water hyacinth for EC (846.1, 699 .00 and 502.1 mg/L), TDS (410.5, 340.0 and 259.0 mg/l), NH3 (1.25, 1.04 and 0.84 mg/l) and Cd (0.021, 0.018 and 0.012 mg/l)., with vetiver grass for EC (828.2, 654.1 and 488.1mg/L), TDS (398.6, 282.8 and 198.2 mg/L), COD (476.5, 355.5 and 265.5 mg/L), NO3 (3.34, 2.13 and 1.40mg/L), TSS (11.6, 8.66 and 6.58mg/L) and Cd (0.019, 0.011 and 0.01mg/L)., and with water lettuce for EC (833.0, 709.6 and 587 mg/L), TDS (452.6, 404.0 and 284.0 mg/L), Cr (0.12, 0.10, and 0.79mg/L), Pb (0.21, 0.18 and 0.13mg/L) and Cd (0.019, 0.013 and 0.011 mg/l). Vetiver grass was found to be more prospective in the curtailment of contaminants.

Reproducibility of peak moment for isometric and isokinetic knee extension exercise

BackgroundAccurate measurements of muscular performance are important for diagnostics, for example during rehabilitation after traumatic injuries but also in competitive sports. For these purposes, dynamometric devices are widely used and considered the gold standard for muscle strength testing. However, few previous studies have tested the reproducibility of peak moment (PM) at velocities close to the maximum device capability, and in general, reproducibility results cannot be transferred to other devices or test protocols. The purpose of this study was to evaluate the reproducibility of PM for different isometric and isokinetic knee extension exercises using the IsoMed 2000.MethodsThirty subjects volunteered in three repeated test sessions, including isometric knee extension (100° and 140° knee angle) and isokinetic knee extension (30°/s and 400°/s). Statistical analysis for comparison of sessions two and three included paired sample t-test, calculation of intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Additionally, Bland Altman statistics and corresponding plots were created.ResultsA significant difference between sessions in PM was found for isometric knee extension in one leg (140° left). Reproducibility was high for all conditions with ICC ranging from 0.964 to 0.988 and SEM in the range of 7.6 to 10.5 Nm. Bland Altman statistics revealed a bias between − 7.3 and 0.7 Nm.ConclusionsReproducibility of PM using the IsoMed 2000 was good after an initial familiarization trial with high values of relative reproducibility. Absolute reproducibility can be interpreted as appropriate for most common practical applications.

Simple ePDF: A Pair Distribution Function Method Based on Electron Diffraction Patterns to Reveal the Local Structure of Amorphous and Nanocrystalline Materials.

Amorphous, glassy or disordered materials play important roles in developing structural materials from metals or ceramics, devices from semiconductors or medicines from organic compounds. Their local structure is frequently similar to crystalline ones. A computer program is presented here that runs under the Windows operating system on a PC to extract pair distribution function (PDF) from electron diffraction in a transmission electron microscope (TEM). A polynomial correction reduces small systematic deviations from the expected average Q-dependence of scattering. Neighbor distance and coordination number measurements are supplemented by either measurement or enforcement of number density. Quantification of similarity is supported by calculation of Pearson's correlation coefficient and fingerprinting. A rough estimate of fractions in a mixture is computed by multiple least-square fitting using the PDFs from components of the mixture. PDF is also simulated from crystalline structural models (in addition to measured ones) to be used in libraries for fingerprinting or fraction estimation. Crystalline structure models for simulations are obtained from CIF files or str files of ProcessDiffraction. Data from inorganic samples exemplify usage. In contrast to previous free ePDF programs, our stand-alone program does not need a special software environment, which is a novelty. The program is available from the author upon request.

Cross-cultural adaptation and validation for central sensitization inventory: based on Chinese patients undergoing total knee arthroplasty for knee osteoarthritis

BackgroundThis study was conducted to develop a simplified Chinese version of the central sensitization inventory (CSI-CV) and to evaluate its reliability and validity.MethodsThe CSI-CV was developed through a process involving the translation and back translation of the original CSI. Subsequently, experts reviewed and revised the content of the items to ensure their appropriateness. A total of 325 patients with knee osteoarthritis (KOA), who were scheduled to undergo total knee arthroplasty (TKA), completed the CSI-CV at a prominent orthopedic center in Xi'an, China. Afterward, a random selection of 100 participants was chosen for retesting after one week. The reliability and validity of the inventory were evaluated through exploratory factor analysis, correlation coefficient calculation and other methods.ResultsThe CSI-CV consists of 25 items in five dimensions (emotional distress, headache and jaw symptoms, physical symptoms, urological symptoms, and fatigue and sleep problems). The cumulative variance contribution rate was 75.3%, the Cronbach's α coefficient was 0.83, the Guttman split-half reliability coefficient was 0.88 and the intraclass correlation coefficient was 0.965. The CSI-CV scores correlated moderately with the total scores of the brief pain inventory (r = 0.506), Western Ontario and McMaster Universities Osteoarthritis Index (r = 0.466) and EuroQoL Group's five-dimension questionnaire (r = 0.576).ConclusionsThe findings demonstrate that the CSI was successfully trans-culturally adapted into a simplified Chinese version (CSI-CV) that was reliable and valid for Chinese-speaking patients who awaiting TKA for KOA.

Factors of job satisfaction and its effects on employee performance: A Case Study of Ghazni University employees

Purpose - This study delves into the factors impacting job satisfaction and their subsequent effects on employee performance within the context of Ghazni University. Aims - In addition, the research also strives to assess the extent of job satisfaction and pinpoint the factors that might lead to job attrition. Design/methodology/approach - To achieve the stated goals; the participant combine comprised 110 university employees’ staff, selected through the Yamane sampling method. Employing an applied research approach, the study adopted a survey-based descriptive methodology, using a questionnaire for data collection. For analysing data using SPSS software, involving calculations of Pearson's correlation coefficient and regression analysis. Findings - The study's outcomes uncover a discernible and moderate connection (correlation coefficient of 0.589) between job satisfaction and the performance of employees. Notably, organizational factors have the most impact performance (correlation coefficient of 0.697). Group factors, demonstrate the coefficient of (0.524) with performance. And collaborative management factors exhibit a coefficient of (0.314) in correlation with performance. A more in-depth analysis of the individual components within the aforementioned factors underscores that compensation and benefits exert the most pronounced effect on both job satisfaction and employee performance. Limitations of the study - The main limitation and challenge in conducting this research was the lack of cooperation in sharing information, Still, due to the specialization of the subject, it required more understanding. Originality/value - This study offers significant insights into the essential nexus between job satisfaction and employee performance. The outcomes emphasize the pivotal role of organizational factors in nurturing both job satisfaction and overall job performance. These findings hold the potential to guide university administrators and policymakers in devising strategies aimed at elevating employee contentment, involvement, and output, thereby playing a pivotal role in bolstering the university's accomplishments and operational efficiency.