Pearson Correlation Coefficient Research Articles

Algorithms and Resources for the Monitoring of Very-Low-Frequency Signal Deviations Due to Solar Activity Using a Web-Based Software-Defined Radio-Distributed Network.

This work presents the development and testing of an experimental web-based SDR (software-defined radio) monitoring system for indirect solar activity detection, which has the ability to estimate and potentially predict various events in space and on earth, including solar flares, coronal mass ejections, and geomagnetic storms. The proposed system can be used to investigate the effect of solar activity on the propagation of very-low-frequency (VLF) signals. The advantages and benefits of the given approach are as follows: increasing measurement accuracy and eventual solar activity identification by combining measurements from multiple spatially distributed SDRs. The verification process involves carrying out several experiments comparing data from the GOES satellite system and the Dunksin SuperSID system with information received by the SDR monitoring system. Then, utilizing Pearson correlation coefficients, the measured data from the SDRs, along with those from the GOES satellite system and the Dunsing monitoring station, are investigated. At the time of a solar flare, the correlation value is above 90% for most of the stations used. Combining the signal-to-noise ratio via summation also shows an improvement in the results, with a correlation above 98%.

AI-driven generalized polynomial transformation models for unsupervised fundus image registration.

We introduce a novel AI-driven approach to unsupervised fundus image registration utilizing our Generalized Polynomial Transformation (GPT) model. Through the GPT, we establish a foundational model capable of simulating diverse polynomial transformations, trained on a large synthetic dataset to encompass a broad range of transformation scenarios. Additionally, our hybrid pre-processing strategy aims to streamline the learning process by offering model-focused input. We evaluated our model's effectiveness on the publicly available AREDS dataset by using standard metrics such as image-level and parameter-level analyzes. Linear regression analysis reveals an average Pearson correlation coefficient (R) of 0.9876 across all quadratic transformation parameters. Image-level evaluation, comprising qualitative and quantitative analyzes, showcases significant improvements in Structural Similarity Index (SSIM) and Normalized Cross Correlation (NCC) scores, indicating its robust performance. Notably, precise matching of the optic disc and vessel locations with minimal global distortion are observed. These findings underscore the potential of GPT-based approaches in image registration methodologies, promising advancements in diagnosis, treatment planning, and disease monitoring in ophthalmology and beyond.

Belief in a just world and fair behavior among clinical nurses: a moderated mediation model of empathy and observer justice sensitivity

BackgroundExploration of the relationship between nursing staffs’ justice in belief world and fair behavior is important to promote equity and access to health services in health organizations, as well as to enhance the quality of care. In order to further dissect the influencing factors of fair behavior among clinical nurses, the current study aims to investigate how belief in a just world influences the fair behavior among nurses. Based on the belief in a just world theory, the empathy-altruism theory and the protective-protective model, the current study aimed to provide a deeper understanding of the effect of belief in a just world on fair behavior by investigating the mediating role of empathy and the moderating role of observer justice sensitivity.MethodThis was a cross-sectional study. 571 registered clinical nurses were included from five hospitals in Fuzhou through a convenience sampling method. Measurements included Chinese translations of belief in a just world scale, empathy scale, observer justice sensitivity scale, fair behavior scale. SPSS 22.0 was used to describe descriptive statistics and the variables’ Pearson correlation coefficient. SPSS PROCESS macro Model 4 and model 14 were used to examine the mediation and the moderation between the relationship of belief in a just world and fairness behavior.ResultThe results shower that fairness behavior was positively correlated with one’s belief in a just world (r = 0.26, p < 0.01); (2)empathy mediated the relationship between belief in a just world and fair behavior. The mediation model explains 20.83%; (3) Observer justice sensitivity moderated the relationship between empathy and fair behavior.ConclusionsBelief in a just world, empathy, and observer justice sensitivity were motivations for nurses’ fair behavior. Nursing administrators should focus on cultivating nurses’ belief in a just world, their empathy abilities, and positive qualities of justice sensitivity to enhance fair behavior in a healthcare setting.

Problem Loans and Working Out the Pinnacle of Bank Failures in Nigeria

This study was designed to evaluate managing problem loans and work out the pinnacle of bank failures in Nigeria. One of the recommendations of the Basel Committee on Banking Supervision was credit risk management which is the optimization of the bank’s risk-adjusted rate of return by maintaining credit risk exposure within an acceptable level. Descriptive survey research was used and data were collected via annual reports of the sampled bank within the period of 2011–2016. The population of the research included the Deposit Money Banks. Pearson Coefficient of Correlation was the statistical tool used to analyse the hypotheses and this was done with the aid of Statistical Package for Social Sciences (SPSS). The researcher concluded that there is no significant relationship between credit risk management and bank failure in Nigeria. However, there were traces of weak negative relationships which keen interest should be given to because of the sensitive nature of the banking sector.

Quality of life and family functioning 12 months after diagnosis of childhood brain tumour: A longitudinal cohort study.

The wellbeing of a child with brain tumour is affected by several factors. We present the first investigation of quality of life and family functioning in a parent and child across the first 12 months after diagnosis, examining potential factors to guide the provision of psychosocial resources to families who most need them. Data were collected from parents/carers in Queensland, Australia, from 2020 to 2023. Child (parent/carer-proxy reported) and carer quality of life was assessed across three timepoints (repeated measures analysis of variance [ANOVA]) and by five potential co-variates (mixed between-within ANOVA). Family functioning was assessed across two timepoints (repeated-measures t-test), and by potential co-variates (repeated measures ANOVA). Univariate relationships were explored with Pearson's correlation coefficient; significant relationships were entered into multiple regression models. Ninety-six diverse families were represented. Quality of life (child, carer) and family functioning did not change across time. Children from households with lower income reported worse cognitive difficulties (p=.023) and pain and hurt (p=.013) than those from a higher income. Caregiver quality of life was poorer for those whose child had received chemotherapy and/or radiation, was aged less than 4 years at diagnosis, and had a lower household income. At 12 months, caregiver quality of life was correlated with family functioning (r=-.45, p<.001), with positive adaptation being a significant key predictor (beta=-.66, p<.005). The following factors indicate a need for increased early psychosocial support: cognitive difficulties, aged<4 years at diagnosis, receiving chemotherapy and/or radiation, and low household income.

Students Attitudes on School Climate and Learning Engagement in Physics of Senior High School Students

This research aims to determine whether there is a substantial correlation between students' attitudes toward school climate and their learning engagement in Physics. It also aims to explore the impact of school climate on Grade 12 students' experiences in attending classes and how it affects learning engagement in Physics. The school climate has an impact on the interactions that exist between educators and students in the classroom. A positive school climate is created where relationships between teachers, students, and the environment are enhanced within the institution. Consequently, the researchers utilized an explanatory mixed-method sequential design. The data collection involved two adapted survey questionnaires, an in-depth interview, and a focus group discussion using simple random sampling with a 335-sample size for quantitative and 10 participants for qualitative. The students' attitudes on school climate acquired an overall mean of 3.89, otherwise described as high, and a 3.98 mean, also described as high, for learning engagement in Physics. The correlation between students' attitudes toward school climate and learning engagement is given by Pearson's correlation coefficient (r) of 0.810, and the associated p-value (P= 0.001), indicating a highly significant correlation. This suggests a comparable rise or fall in school climate as students' attitudes increase or decrease. In the qualitative phase of the study, five main themes emerged from the data which support the quantitative findings and further explain the result of the study.

An Assessment of the Knowledge, Attitude, and Practice of Probiotics and Prebiotics among the Population of the United Arab Emirates.

Probiotics and prebiotics offer a range of advantageous effects on human health. The knowledge, attitudes, and practices (KAP) of individuals can impact their inclination to consume probiotics and prebiotics. The main objective of this study was to examine the KAP of the people in the United Arab Emirates (UAE) about probiotics and prebiotics consumption. Additionally, the study aimed to assess the impact of KAP and sociodemographic factors on the use of probiotics and prebiotics. In order to accomplish this objective, a verified online questionnaire was used with a five-point Likert scale and distributed using an online platform (Google Forms). A cross-sectional research, non-probability sampling was implemented, and G*Power statistical power analysis was used to estimate a sample size of 385 participants. A total of 408 replies were gathered. The population under study consisted of residents in the UAE between the ages of 18 to 64 years old, excluding populations under the age of 18 and those living outside the UAE. A total of 392 participants met the criteria for inclusion in this study. The research ethics committees of UAE University granted the study approval (ERSC_2024_4359), and the validity of the findings was confirmed through face-to-face interviews with around 50 individuals and a Cronbach's alpha test with result of 0.84. The statistical software SPSS version 29.0 for Mac OS was utilized to examine the relationships between KAP variables, including Chi-square tests and Pearson's correlation coefficients. The tests were selected based on their capacity to handle categorical and continuous data, respectively. The female population was 85.2% of the total, while the male population accounts for 14.8%. The age distribution of participants shows that the largest proportion, 68.4%, falls within the 18-24 age range. Out of the participants, 61.5% held a bachelor's degree. Most of the participants, 56.4%, were students, while 29.1% were employees. The average results indicate a significant inclination towards probiotics and prebiotics, as demonstrated by the scores above the midpoint for the six knowledge questions (M = 2.70), six attitude questions (M = 3.10), and six practice questions (M = 3.04). Several studies have examined this phenomenon; however, additional research comparing individuals in the UAE is necessary to fully comprehend the influence of KAP on the consumption of probiotics and prebiotics in the UAE.

Influence of Motivation Climate on Service-Learning Benefits among Physical Education Students

&lt;p style="text-align: justify;"&gt;Service-learning (SL) emphasizes the fusion and integration of community service and academic learning, while Physical Education (PE) is oriented towards community health and well-being, aligning with Sustainable Development Goals. The study's primary objective is to discern the benefits perceived by PE students when engaged in SL courses and to test the correlation between benefits and the motivational climate they experience. Additionally, the research explores potential gender-specific variations in students' attitudes. The research was conducted with a survey on a sample of 58 students responding to a Motivational Climate in Physical Education Scale (MPCES) and the SErvice LEarning Benefit Scale (SELEB), which assesses the motivation of students and their perceptions of SL benefits. Descriptive statistics was used to analyse the data. Pearson's correlation coefficient was used to test the relationship between the core constructs - SL benefits and student motivation, and t-tests to evaluate gender differences in SL benefits. Key findings underscore that students primarily perceived the greatest advantages from SL in the domain of knowledge application, with comparatively lower scores in general life skills. Notably, female students, on the whole, exhibited higher ratings in both SL benefits and student motivation compared to their male counterparts. Nonetheless, specific exceptions emerged in certain sub-scales, including social relatedness and ego climate within the MPCES scale, as well as critical thinking within the SELEB scale. According to the results, it is suggested that cultivating a student-centered learning environment can augment engagement and motivation in the realm of physical education (PE). Furthermore, the delineated gender differences offer valuable insights for educators, highlighting the need for tailored approaches to accommodate the diverse preferences and requirements of male and female students.&lt;/p&gt;

Navigating the Dynamics of Brent Crude Oil Prices: Factors, Trends, and Insights

Accurate Brent Crude Oil price prediction is essential for informed decision-making and risk control in the global energy market. This paper examines the dynamics of Brent Crude Oil prices over the previous 35 years, utilizing predictive modelling techniques to project future prices and analyzing historical trends and relationships with the GDPs of major economies. The statistical methods used in this paper include the moving average and Pearson correlation coefficient. While correlation studies show significant positive links between Brent Crude Oil prices and the GDPs of major economies like China, Saudi Arabia, Europe, Russia, and the United States, historical data analysis reveals large price volatility. Highly accurate price forecasting using LSTM (Long Short-Term Memory) modelling approaches provides detailed risk management and decision-making information in the global energy market. The application of the Neural Network and the ARIMA model shows an increase in the price of Brent crude oil in the next year, 2024. Identifying the importance of the Brent crude oil price forecast and its effect on the international market is highly needed. This paper thus might help to increase economic growth. These results highlight the importance of advanced modelling techniques and economic indicators in managing oil price changes and help make informed decisions in the energy industry.

Inter- and Intra-Observer Variability of the AMADEUS Tool for Osteochondral Lesions of the Talus.

Managing osteochondral cartilage defects (OCDs) of the talus is a common daily challenge in orthopaedics as they predispose patients to further cartilage damage and progression to osteoarthritis. Therefore, the implementation of a reliable tool to quantify the amount of cartilage damage that is present is of the essence. We retrospectively identified 15 adult patients diagnosed with uncontained OCDs of the talus measuring <150 mm2, which were treated arthroscopically with bone marrow stimulation. Five independent assessors evaluated the pre-operative MRI scans with the AMADEUS scoring system (i.e., MR-based pre-operative assessment system) and the intra-/inter-observer variability was then calculated by means of the intraclass correlation coefficients (ICC) and Kappa (κ) statistics, respectively. In addition, the correlation between the mean AMADEUS scores and pre-operative self-reported outcomes as measured by the Manchester-Oxford foot questionnaire (MOxFQ) was assessed. The mean ICC and the κ statistic were 0.82 (95% CI [0.71, 0.94]) and 0.42 (95% CI [0.25, 0.59]). The Pearson correlation coefficient was found to be r = -0.618 (p = 0.014). The AMADEUS tool, which was originally designed to quantify knee osteochondral defect severity prior to cartilage repair surgery, demonstrated good reliability and moderate inter-observer variability for small OCDs of the talar shoulder. Given the strong negative correlation between the AMADEUS tool and pre-operative clinical scores, this tool could be implemented in clinical practise to reliably quantify the extent of the osteochondral defects of the talus.

Borehole Breakout Prediction Based on Multi-Output Machine Learning Models Using the Walrus Optimization Algorithm

Borehole breakouts significantly influence drilling operations’ efficiency and economics. Accurate evaluation of breakout size (angle and depth) can enhance drilling strategies and hold potential for in situ stress magnitude inversion. In this study, borehole breakout size is approached as a complex nonlinear problem with multiple inputs and outputs. Three hybrid multi-output models, integrating commonly used machine learning algorithms (artificial neural networks ANN, random forests RF, and Boost) with the Walrus optimization algorithm (WAOA) optimization techniques, are developed. Input features are determined through literature research (friction angle, cohesion, rock modulus, Poisson’s ratio, mud pressure, borehole radius, in situ stress), and 501 related datasets are collected to construct the borehole breakout size dataset. Model performance is assessed using the Pearson Correlation Coefficient (R2), Mean Absolute Error (MAE), Variance Accounted For (VAF), and Root Mean Squared Error (RMSE). Results indicate that WAOA-ANN exhibits excellent and stable prediction performance, particularly on the test set, outperforming the single-output ANN model. Additionally, SHAP sensitivity analysis conducted on the WAOA-ANN model reveals that maximum horizontal principal stress (σH) is the most influential parameter in predicting both the angle and depth of borehole breakout. Combining the results of the studies and analyses conducted, WAOA-ANN is considered to be an effective hybrid multi-output model in the prediction of borehole breakout size.

Fetal Gestational Age Prediction in Brain Magnetic Resonance Imaging Using Artificial Intelligence: A Comparative Study of Three Biometric Techniques

Accurately predicting a fetus’s gestational age (GA) is crucial in prenatal care. This study aimed to develop an artificial intelligence (AI) model to predict GA using biometric measurements from fetal brain magnetic resonance imaging (MRI). We assessed the significance of using different reference standards for interpreting GA predictions. Measurements of biparietal diameter (BPD), fronto-occipital diameter (FOD), and head circumference (HC) were obtained from 52 normal fetal MRI cases from Rush University. Both manual and AI-based methods were utilized, and comparisons were made using three reference standards (Garel, Freq, and Bio). The AI model showed a strong correlation with manual measurements, particularly for HC, which exhibited the highest correlation with actual values. Differences between GA predictions and picture archiving and communication system (PACS) records varied by reference, ranging from 0.47 to 2.17 weeks for BPD, 0.46 to 2.26 weeks for FOD, and 0.75 to 1.74 weeks for HC. Pearson correlation coefficients between PACS records and GA predictions exceeded 0.97 across all references. In conclusion, the AI model demonstrated high accuracy in predicting GA from fetal brain MRI measurements. This approach offers improved accuracy and convenience over manual methods, highlighting the potential of AI in enhancing prenatal care through precise GA estimation.

An Improved Dempster–Shafer Evidence Theory with Symmetric Compression and Application in Ship Probability

Auxiliary information sources, a subset of target recognition data sources, play a significant role in target recognition. The reliability and importance of these sources can vary, thereby affecting the effectiveness of the data provided. Consequently, it is essential to integrate these auxiliary information sources prior to their utilization for identification. The Dempster-Shafer (DS) evidence theory, a well-established data-fusion method, offers distinct advantages in handling and combining uncertain information. In cases where conflicting evidence sources and minimal disparities in fundamental probability allocation are present, the implementation of DS evidence theory may demonstrate deficiencies. To address these concerns, this study refined DS evidence theory by introducing the notion of invalid evidence sources and determining the similarity weight of evidence sources through the Pearson correlation coefficient, reflecting the credibility of the evidence. The significance of evidence is characterized by entropy weights, taking into account the uncertainty of the evidence source. The proposed asymptotic adjustment compression function adjusts the basic probability allocation of evidence sources using comprehensive weights, leading to symmetric compression and control of the influence of evidence sources in data fusion. The simulation results and their application in ship target recognition demonstrate that the proposed method successfully incorporates basic probability allocation calculations for ship targets in various environments. In addition, the method effectively integrates data from multiple auxiliary information sources to produce accurate fusion results within an acceptable margin of error, thus validating its efficacy. The superiority of the proposed method is proved by comparing it with other methods that use the calculated weights to weight the basic probability allocation of the evidence sources.

Enzyme inhibiting, antibacterial and antioxidant activities of peel, pulp and seed extracts from dau Ha Chau (Baccaurea ramiflora Lour.) fruit of Vietnam

Dau Ha Chau (DHC) was produced by selecting and growing native kinds of Baccaurea ramiflora Lour. in Vietnam, where the fruit is utilized for fresh eating not only due to its distinctive sour-sweet flavor, but also because of its vitamins and minerals for the body. With the aim to enhance the value of this fruit, the peel, pulp, and seed extracts were determined antioxidant, antibacterial and antidiabetic activities. The filtrates from ethanol extract of peel and seed powders and fruit juice from squeezing pulp were evaporated at 58°C to create the extracts. The six methods of TAC, DPPH, ABTS•+, RP, FRAP, and NO• (antioxidant activities), four bacterial strains and two enzymes (associated with type 2 diabetes mellitus) were evaluated. The results showed that the extract of DHC peel exhibited the highest antioxidant activity (EC50 value from the six methods), antibacterial activity (MIC value), enzyme inhibiting activity (IC50 value), total phenolics content and total flavonoids content, at 643.81 µg/mL, 787.42 µg/mL, 651.10 µg/mL, 718.22 µg/mL, 270.38 µg/mL, 662.44 µg/mL, 16 &lt; MIC ≤ 32 mg/mL (against Propionibacterium acnes, Escherichia coli and Bacillus cereus), 32 &lt; MIC ≤ 64 mg/mL (against Staphylococcus aureus), 2780.91 µg/mL (against α-amylase), 541.24 µg/mL (against α-glucosidase), 119.43 mg GAE/g and 207.17 mg QE/g, respectively, whereas the opposite was true for extract of DHC seed. DHC pulp extract came second in all analytical methods. Pearson correlation coefficients with r value (0.63-0.99) showed a reasonably strong relationship between total phenolics and flavonoids contents, and antioxidant and enzyme inhibiting activities. This is the first report on the antioxidant, antibacterial and antidiabetic activities of DHC Ha Chau fruit extracts, which could be developed for medicinal, pharmaceutical, food preservative purposes, or industrial foods in the future.

The effectiveness of using a proposed model of contemplative learning on developing metacognitive skills and the achievement of eleventh grade female students in physics

The study aimed to investigate the effectiveness of using a proposed model of contemplative learning on developing metacognitive skills and the achievement of eleventh grade female students in physics, in Muscat Governorate, Sultanate of Oman. The study sample consisted of (53) female students, who were distributed into two groups: an experimental group, consisting of (25) female students, and a control group, consisting of (28) female students. To answer the study questions, the Schraw and Dennison scale for knowledge organization skills was used, and its reliability coefficient value was (0.90). An achievement test was prepared and its validity was confirmed, and the Pearson correlation coefficient value was (0.91), which is a good indicator for the study. The study found that there were no statistically significant differences between the average scores of the female students of the two study groups at the significance level (α = 0.05) in the overall knowledge organization skills and sub-skills, while there were statistically significant differences between the average scores of the female students of the two study groups at the significance level (α = 0.05) in the total score of the academic achievement test, as well as in the levels of application and reasoning between the experimental and control groups in favor of the experimental group, while there is no statistically significant difference at the significance level (α = 0.05) between the average scores of the female students of the two study groups in the level of knowledge. The study recommended the need to hold training workshops to introduce contemplative learning, integrate contemplative learning methods in building physics and science curricula, and benefit from study tools and materials and apply them in the educational field. Keywords: reflective learning - metacognitive skills - academic achievement

신규간호사를 대상으로 프리셉터와의 교환관계가 자기효능감, 회복탄력성 및 직무만족도에 미치는 영향

Objectives This study examined the effects of the exchange relationship with a preceptor on self-efficacy, resilience, and job satisfaction among new nurses. Methods Data were collected from 125 new nurses in a hospital in City S by questionnaire after 8 weeks of preceptor-ship. Data were analyzed using t-test, one-way analysis of variance, Pearson correlation coefficient analysis, and linear regression analysis. Results The exchange relationship between new nurses and preceptors was statistically significantly correlated with self-efficacy(p=.024), resilience(p=.003), and job satisfaction(p＜.001). The higher the relationship between new nurses and preceptors, the higher the self-efficacy (B=0.281, p=.024), resilience (B=0.304, p=.003), and job satisfaction (B=0.507, p&lt;.001). Conclusions The results of this study showed that the higher the relationship between new nurses and their preceptors, the higher their self-efficacy, resilience, and job satisfaction. Therefore, it is necessary to provide education and self-development for preceptors so that they can play the role of role model, emotional support, and counselor as well as educator to new nurses.

Provenance composition and evolution of marine black shales in the Yangtze platform from Ediacaran to Silurian

Provenance is important in understanding the evolution of geological structure and the coupling of the basin-mountain system. Although many geochemical data document the three sets of marine black shales (Ediacaran to Silurian) in the Yangtze Platform, the evolution characteristics of their sediment sources remain unclear. We gather a huge database from 307 published papers totaling 12,342 analyzed samples to establish provenance. Pearson correlation coefficient and multivariate statistical analyses were performed to establish the element and mineral links in the black shale. Nine immobile elemental ratios (Ti/Th, Th/Sc, Cr/Th, Ti/Zr, Sc/Ta, Ti/Nb, Sc/La, Zr/Sc, and La/Ti) were employed to indicate provenance. The results show that the black shales of the Longmaxi and Niutitang formations are relatively enriched in redox sensitive and productivity related elements such as V, Cr, Mo, U, Co, Ni, Cu, Zn, and Ba. The use of provenance analysis proxies, including V, Cr, Mo, Ce, Fe, P, Ba, Cu, Ni, and Si, should be approached with caution due to the potential interference of marine authigenic components. The three black shales have provenance compositions that gradually extend from intermediate to felsic from the Doushantuo to the Niutitang to the Longmaxi shale. This difference in provenance is a response to the Pan-African and Kwangsian orogenic structures which are likely to impact the paleomarine environment by variable biotrophic element inputs.

Body image, illness uncertainty and symptom clusters in surgically treated breast cancer survivors: An exploratory factor analysis and correlational study

PurposeTo determine the relationship among body image, illness uncertainty, and symptom clusters in surgically treated breast cancer survivors. MethodsA correlational, descriptive study was conducted in a convenience sample of 60 women surgically treated breast cancer survivors recruited in a private hospital and a survivor center. A questionnaire of sociodemographic characteristics, MUIS-C Scale, and QLQ-C30 and Module BR-23 were used. Variable characteristics and associations were analyzed with descriptive statistics and Pearson correlation coefficient, and exploratory factor analysis using unweighted least squares and Promax rotation was used for symptom clustering. ResultsA three-factor structure was found: an anxiety symptom cluster, a breast symptom cluster, and an arm symptoms, depression, and fatigue symptom cluster, explaining 46,47% of the variance. Significant correlations were found among body image and illness uncertainty (r = −0,390, p < 0,01), body image and the anxiety symptom cluster (r = 0,613, p < 0,01), illness uncertainty and the anxiety symptom cluster (r = −0,421, p < 0,01), the breast symptom cluster (r = −0,425, p < 0,01), and the arm symptoms – depression – fatigue symptom cluster (r = −0,443, p < 0,01). ConclusionThe relationships among all variables were statistically significant. Nurses providing care to BC survivors need to address the multidimensionality of the symptom experience and its correlates to better assist their patients. Further research is needed to elucidate the biopsychosocial underpinnings of those relationships.

Construction and Validation of a Cognitive Engagement Scale and Its Relationship with Ball Movement Sequence Performance in Rhythmic Gymnastics

The research aims to: build and record a measure of cognitive participation among second-year female students at the College of Physical Education and Sports Sciences, University of Baghdad. The researchers used the descriptive approach in the survey style for the research sample. The sample was selected from female students and divided into: (10) female students for the survey sample, and (80) female students for the construction and codification sample. The data were statistically analyzed by the researchers using SPSS, the T-test for independent and correlated samples, Pearson's simple correlation coefficient, Cronbach's alpha, Chi-square, and Spearman-Brown. They were recruited for the samples. The study concluded that constructing a measure of cognitive participation for students in the second stage could be applied through the ease and difficulty of its expressions that are appropriate to the research sample, as well as the grades and levels that were reached, which showed that the sample fell within the rating (good and acceptable), and on the other hand the sample was characterized by participation. Cognitive through the results of the scale and its four axes. In conclusion, cognitive participation plays a positive role in performing the ball movement sequence in rhythmic gymnastics.

Demirjian's and Cameriere's Methods for the Assessment of Dental Age Estimation in Children from a Southern Brazilian City.

The chronological age estimation of living individuals is a crucial part of forensic practice and clinical practice, such as in orthodontic treatment. It is well-known that methods for age estimation in living children should be tested on different populations. Ethnic affiliations in Brazil are divided into several major groups depending on the region, with the south of Brazil being known for its German immigration. (1) Background: This study aimed to evaluate the correlation between chronological age and dental age using Demirjian's method and Cameriere's method in a group of children from Joinville, South Brazil to investigate if both methods can be used to estimate dental age in this population. (2) Methods: The sample consisted of 229 panoramic radiographs (119 were males and were 110 females) from Brazilian children (ages ranging from 6 to 12 years). The chronological age at the time of the panoramic radiographic exam was calculated for each child. The dental age was estimated according to Demirjian's method and Cameriere's method. All continuous data were tested for normality by using the Shapiro-Wilk test. The Pearson correlation coefficient test was applied. An alpha of 5% (p < 0.05) was used for all analyses. (3) Results: The mean chronological age was 8.75 years. According to Demirjian's method, the mean dental age was 9.3 years, while according to Cameriere's method, the mean dental age was 8.66 years. A strong correlation between chronological age and dental age according to Demirjian (r = 0.776 and p < 0.0001) and Cameriere (r = 0.735 and p < 0.0001) was observed for both genders. (4) Conclusions: Both methods presented a good correlation with chronological age in the studied population and could be used to assess dental age in this population.