Skewness Values Research Articles

Differences in apparent diffusion coefficient histogram analysis according to EGFR mutation status in brain metastasis due to lung adenocarcinoma.

The etiology, clinicopathological features, and prognosis of cancer in cases with EGFR mutations are different from those without mutations.OBJECTİVE:This study aims to evaluate the differences in ADC histogram analysis in brain metastases with EGFR mutation status in lung adenocarcinoma cases and the relationship between ADC histogram analysis differences and overall survival. In this retrospective case-control study, 30 patients (8 EGFR+/22 EGFR-) and 51 brain metastases (15 EGFR+/36 EGFR-) were included. ROI markings are first performed from each section, including metastasis in ADC mapping using FIREVOXEL software. Next, ADC histogram parameters are calculated. Overall survival analysis after brain metastasis (OSBM) is defined as the time from initial brain metastasis diagnosis to the time of death or last follow-up. Patient-based (by evaluating the largest lesion) and lesion-based (by evaluating all measurable lesions) statistical analyses are then performed. In the lesion-based analysis, skewness values are lower in EGFR+ patients, which is statistically significant (p = 0.012). The two groups have no significant difference regarding other ADC histogram analysis parameters, mortality, and overall survival (p > 0.05). In the ROC analysis, the most appropriate skewness cut-off value is determined as 0.321 to distinguish the EGFR mutation difference, and this value is statistically significant (sensitivity: 66.7%, specificity: 80.6%, AUC: 0.730) (p = 0.006).CONCLUSİON:The findings of this study provide valuable insights into the differences in ADC histogram analysis according to EGFR mutation status in brain metastases due to lung adenocarcinoma. The identified parameters, especially skewness, are potentially non-invasive biomarkers for predicting mutation status. Incorporating these biomarkers into routine clinical practice may aid treatment decision-making and prognostic assessment for patients. Further validation studies and prospective investigations are warranted to confirm the clinical utility of these findings and establish their potential for personalized therapeutic strategies and patient outcomes.

Analysis of attitudes of students attending secondary education institutions towards physical education and sports according to various variables

The aim of this study is to examine the attitudes of students in secondary education institutions towards physical education and sports according to various variables. In this quantitative study, a survey model was used. The study group consists of students in secondary education institutions affiliated to the Ministry of National Education. The sampling group, which was determined by convenient sampling method, consists of 387 people in total, 174 girls and 213 boys. In the first part of the measurement tool consisting of two parts; there is a personal information form that includes questions about the demographic information of the participants such as gender, licensed sports status, participation in school sports, income and class. The second part involves the Attitude Scale on Physical Education and Sports (BESITO) developed by Deliceoğlu (2018) to measure the participants' attitudes towards physical education and sports. Normality tests were applied to the data obtained and it was assumed that the data showed normal distribution since Skewness and Kurtisos values were between -2 and +2. Later, independent sample (T-Test) and one-way variance (One-Way ANOVA) tests were applied. Welch values were taken into consideration for the data that did not show homogeneity in the One-Way ANOVA test, and Tukey HSD test, one of the Post Hoc tests, was applied as the second step test. The results obtained were evaluated at 0.05 significance level. While no significant difference was found depending on gender and income variables, a significant difference was found in the behavioural sub-dimension depending on the variable of being a licensed athlete. A statistically significant difference was found in both behavioural and Besito total scores according to participation in school sports. Finally, a statistically significant difference was found in the affective sub-dimension depending on the class variable. As a result, in the study in which we examined the attitudes of students in secondary education institutions towards physical education and sports, it was concluded that students' attitude scores may differ according to various variables.

Evaluating and quantifying the variations and sensitivity in asphalt-filler interaction indices

The interaction within an asphalt-filler blend is usually defined by its volume filling and interfacial reciprocation tendencies. This interplay between a reinforcing solid filler within liquid asphalt thus ends up dictating the blend's transition point from a “diluted region” to a “concentrated region”, and the glass transitioning state of the asphalt itself. While prior studies focused on distinguishing asphalt-filler interactions based on composite reinforcement models, describing the definitive behaviour of its suffusing phase reciprocation has proved elusive. Hence, this study aims at redefining asphalt-filler interaction by evaluating and quantifying the varying distinctions in each established mastic composite model. Asphalt mastics composed of three distinct fillers of dolomite powder (DP), lime kiln dust (LKD), and ordinary Portland cement (OPC), along with a conventional PEN 60/70 binder, were blended together at 0.4, 0.8, and 1.2 filler to binder ratios (F/B) based on the Superpave mix dust to binder specification. The OPC mastic was regarded as the control mastic sample for all tests performed. A temperature sweep test was conducted on all prepared mastic test samples using dynamic shear rheometer equipment at varying temperatures of 46 °C, 52 °C, 58 °C, 64 °C, 70 °C, 76 °C, and 82 °C, for a controlled strain value of 5%, and an angular velocity of 10 rad/s. Asphalt-filler interaction was further analysed using evaluation index coefficients based on rheological performances, i.e., ΔG*, L-A-δ, K-B-δ, K-B-G*, and KE respectively. Variations in the evaluation coefficients obtained were also determined via statistical normality tests of skewness and kurtosis. Results obtained indicated a strong asphalt-filler interaction response for coefficients ΔG*, L-A-δ, K-B-G*, and KE, while K-B-δ exhibited inconsistent interaction responses. Similarly, the normality test results also inferred that ΔG*, L-A-δ, K-B-G*, and KE portrayed better skewness values compared to K-B-δ.

Amyotrophic lateral sclerosis with upper motor neuron predominance: diagnostic accuracy of qualitative and quantitative susceptibility metrics in the precentral gyrus.

The study aims at comparing the diagnostic accuracy of qualitative and quantitative assessment of the susceptibility in the precentral gyrus in detecting amyotrophic lateral sclerosis (ALS) with predominance of upper motor neuron (UMN) impairment. We retrospectively collected clinical and 3T MRI data of 47 ALS patients, of whom 12 with UMN predominance (UMN-ALS). We further enrolled 23 healthy controls (HC) and 15 ALS Mimics (ALS-Mim). The Motor Cortex Susceptibility (MCS) score was qualitatively assessed on the susceptibility-weighted images (SWI) and automatic metrics were extracted from the quantitative susceptibility mapping (QSM) in the precentral gyrus. MCS scores and QSM-based metrics were tested for correlation, and ROC analyses. The correlation of MCS score and susceptibility skewness was significant (Rho = 0.55, p< 0.001). The susceptibility SD showed an AUC of 0.809 with a specificity and positive predictive value of 100% in differentiating ALS and ALS Mim versus HC, significantly higher than MCS (Z = -3.384, p-value = 0.00071). The susceptibility skewness value of -0.017 showed specificity of 92.3% and predictive positive value of 91.7% in differentiating UMN-ALS versus ALS mimics, even if the performance was not significantly better than MCS (Z = 0.81, p = 0.21). The MCS and susceptibility skewness of the precentral gyrus show high diagnostic accuracy in differentiating UMN-ALS from ALS-mimics subjects. The quantitative assessment might be preferred being an automatic measure unbiased by the reader. The clinical diagnostic evaluation of ALS patients might benefit from the qualitative and/or quantitative assessment of the susceptibility in the precentral gyrus as imaging marker of upper motor neuron predominance. • Amyotrophic lateral sclerosis diagnostic work-up lacks biomarkers able to identify upper motor neuron involvement. • Susceptibility-weighted imaging/quantitative susceptibility mapping-based measures showed good diagnostic accuracy in discriminating amyotrophic lateral sclerosis with predominant upper motor neuron impairment from patients with suspected motor neuron disorder. • Susceptibility-weighted imaging/quantitative susceptibility mapping-based assessment of the magnetic susceptibility provides a diagnostic marker for amyotrophic lateral sclerosis with upper motor neuron predominance.

Development of a nomogram based on pericoronary adipose tissue histogram parameters to differentially diagnose acute coronary syndrome

PurposeTo develop a nomogram based on pericoronary adipose tissue (PCAT) histogram parameters to identify patients with acute coronary syndrome (ACS). Materials and methodsThis study retrospectively enrolled 114 and 383 eligible patients with ACS and stable coronary artery disease (CAD), respectively, and divided them into training and testing cohorts in a 7:3 ratio. A blinded radiologist obtained PCAT histogram parameters from the right coronary artery's proximal segment using fully automated software and compared clinical characteristics and PCAT histogram parameters between the two patient groups. The binary logistic regression included significant parameters (P < 0.05), and a nomogram was constructed. ResultsIn both the training and testing cohorts, the mean, 10th percentile, 90th percentile, median, and minimum values of PCAT were higher, and the interquartile range, skewness, and variance values of PCAT were lower in patients with ACS than in those with stable CAD (P ≤ 0.001). The mean (OR = 4.007), median (OR = 0.576), minimum (OR = 0.893), skewness (OR = 85,158.806) and variance (OR = 1.013) values of PCAT were independent risk factors for ACS and stable CAD in the training cohort. The nomogram was constructed using the five variables mentioned above with area under the curve values of 0.903 and 0.897, respectively, while the calibration and decision curves showed the nomogram's good clinical efficacy for the training and testing cohorts. ConclusionsThe constructed nomogram had good discrimination and accuracy and can be a noninvasive tool to intuitively and individually distinguish between ACS and stable CAD.

Quantitative Evaluation of the Spatial Variation of Surface Soil Properties in Continuous Paddy Growing Fields

Soil degradation caused by poor land management practices is a major impediment to optimal land productivity. Soil spatial variability is required for agricultural productivity, food safety and environmental modeling. Rice is one of the important food resources for most of the world’s population, especially in India and feeds more than 60 per cent population of the country. Telangana is on track to become India's rice bowl as rice production is expected to reach 1.3 crore tons in 2019–20.The present study was conducted in continuous paddy cultivated field of Machapur village of Siddipet district, Telangana, India to know the spatial variability of soil properties with a help of geostatistical model. For this, a total of 100 composite samples at 20*20 m grids in an area of 4 ha were collected. The pH of the soil, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P) and potassium (K) were all determined. The semivariogram model was used to create surface maps of soil properties using the ordinary kriging technique. The skewness values showed a normal distribution for all analyzed parameters except for Available K. Coefficient of variation ranged from 1.92% for pH to 34.08% for EC in topsoil indicating the heterogeneity of soil properties. Spherical model fits well with experimental semivariogram of pH, EC and AK. Exponential model better described the variation of soil OC and AN while the variation of AP was best described by Gaussian model. The soil pH, OC and available P were moderately spatially dependent whereas EC, available N and K were strongly spatially dependent. The cross validation results demonstrated the spatial prediction's smoothing effect. According to the findings of this study, a geostatistical model can directly reveal the spatial variability of lateritic soils and will assist farmers and decision makers in improving soil-water management.

Examining The Attitudes Of Amateur Football Players Towards Football

In this study, it is aimed to examine the attitudes of amateur football players towards football. The study group of the research consists of 194 football players who play football actively in Sivas and Yalova provinces in the 2021-2022 season. Data collection in the study consists of two parts. In the first part, the personal information form created by the researchers was used, and in the second part, the Football Attitude Scale (FUTÖ) scale, which Kayapınar and Kaan's validity and reliability were made (2021), was used. In the analysis of the data in this study, the SPSS 25.00 package program was used, and it was evaluated at the 95% confidence interval and at the 0.05 significance level. Descriptive statistics were calculated regarding age, gender, educational status, geographical region, province and the position information of the participants in football. It was decided whether the data showed a normal distribution or not by looking at the kurtosis skewness values. In terms of statistics, Independent Sample t test, Anova test, frequency, percentage and reliability coefficient calculations were made. As a result; When the attitudes of the participants towards football in the gender variable are examined, there is a statistically significant difference in favor of the female participants between the scale total score and the sub-dimensions of the scale, social effects, performance, and psychological effects. It was seen that there was a statistically significant difference in the sub-dimensions, and there was no statistically significant difference between the province and location variables, the total score of the scale and all sub-dimensions.

The Effect of Steel Electropolishing on the Tribological Behavior of a Steel–Bronze Pair in the Mixed and Boundary Lubrication Regimes

Electropolishing at high current densities without agitation of the electrolyte results in a pitting phenomenon that produces dimple-like surface features. Although pitting is unfavorable in the electropolishing process, its effect on surface modification, such as surface texturing, has not been thoroughly investigated. Surface topography and chemical composition analyses of electropolished steel revealed surface pits and an oxide surface layer, indicating the presence of surface texture and coating. The resulting surface is characterized by negative skewness and high kurtosis values. The tribological behavior of the electropolished steel-bronze pair is investigated by evaluating coefficients of friction and bronze wear using sliding tests conducted in mixed and boundary lubrication regimes. The results are compared to those of the ground steel-bronze pair. In the mixed and upper range of the boundary lubrication regime, coefficients of friction reduction up to 30% and shorter running-in phases are observed for electropolished steel (electropolished steel μavg = 0.019 vs. ground steel μavg = 0.028). In contrast, the coefficient of friction increased in the lower range of boundary lubrication regime by 50% (electropolished steel μavg = 0.098 vs. ground steel μavg = 0.065). Electropolishing, as a cost- and time-effective method applicable to complex geometries, presents an alternative method for achieving surface modifications aimed at friction reduction and improved tribological behavior for non-conformal contacts in the boundary and mixed lubrication regimes.

Micro-grit blasting to enhance adhesion of diamond coating on Ti6Al4V

Diamond coatings are of industrial importance due to their tribological properties like wear resistance and low friction. These properties can be exploited only when the coating has good adhesion to the substrate. Substrates such as titanium alloys exhibits poor adhesion due to differences in the coefficient of thermal expansion (CTE) between the diamond coating and the substrate. This study investigates the enhancement of diamond coating adhesion to substrate by micro-grit blasting. The effect of micro-grit blasting pressure and angle of blasting are systematically studied. The micro-grit blasted surface is characterised by the roughness parameters such as skewness and kurtosis. Diamond coating is carried out on the grit-blasted substrates using the hot filament chemical vapour deposition (HFCVD) method and then characterised using electron microscopy, Raman spectroscopy, X-ray diffraction, and scratch testing. The skewness was seen to be negative, and did not vary much with grit-blasting conditions. A high value of residual stress has been observed in all the samples. Pressure was inversely correlated with kurtosis and is one of the dominant factors influencing kurtosis variation. Surfaces with lower kurtosis value were found to have higher adhesion strength. The effect of angle on adhesion depends on the relative value of skewness at the given angle. Adhesion strength is proportional to the skewness in the case of angle variation. The crystal size of the diamond grown for both parameters (angle & pressure) initially increases and then decreases depending on the surface free energy. Higher the surface free energy lower will be the average crystal size.

Application of deep learning-based CT texture analysis in TNM staging of gastric cancer

ObjectiveTo analyze the application of deep learning computed tomography (CT) texture analysis in TNM staging of gastric cancer. MethodsUse deep learning software networks to select GoogLeNet and AlexNet models that perform well in image classification work to diagnose gastric cancer pathological images. Based on the characteristics of pathological medical images, the GoogLeNet model was optimized to reduce computational costs while ensuring diagnostic accuracy. On this basis, model fusion is proposed, which integrates network models with different structures and depths to learn more image features and obtain more useful pathological information about gastric cancer. ResultsA deep convolutional neural network was used to automatically classify gastric cancer pathological images using AlexNet and GogLeNet models with significant structural differences. It can be seen that the model achieved high diagnostic accuracy, with a sensitivity of 97.60% and a specificity of 99.49%. However, the experimental method relied more on manually selected pathological features of gastric cancer. The AUC values of maximum frequency, skewness, and kurtosis during the venous phase were 0.735, 0.711, and 0.720, respectively (all P < 0.05). ConclusionThe improved model has the characteristics of both network structures and is more targeted at gastric cancer pathological sections, improving the sensitivity of gastric cancer pathological section recognition. Therefore, deep learning for CT texture analysis can effectively evaluate gastric cancer TNM staging and guide clinical treatment for diagnosing gastric cancer, which has a positive significance.

피지컬 리터러시 내 동기 및 자신감 영역 척도에 관한 타당성

Objectives The purpose of this study was to verify the validity of the Korean CAPL-2 questionnaire scale, which translates the Canadian Assessment of Physical Literacy-Second Edition questionnaire for measuring the motivation and confidence domain within Physical Literacy.&#x0D; Methods The subjects consisted of 163 students (male : 91 and female : 72) from the 3rd to 6th grade at a public elementary school located in D city of Korea. The Korean CAPL-2 psychological measurement questionnaire scale was completed through translation, reverse translation, and content review by expert groups, and data were collected using the Korean CAPL-2 questionnaire scale. For data analysis, exploratory factor analysis, confirmatory factor analysis, and construct validity analysis were performed, using SPSS 26 and AMOS 27 statistical program.&#x0D; Results The results showed that first, the range of the total score of the study participants was 10.6 to 30.0, and the average value was 23.60 points. The skewness (-0.59) and kurtosis (0.03) values showed a normal distribution closed to 0, and the correlation range between the four sub-factors was between .468 and .650. Second, confirmatory factor analysis results for the Korean CAPL-2 questionnaire scale chi-square(χ2)/df 1.543, RMSEA .058, RMR .012, GFI .929, IFI .976, TLI .967, and CFI .976, all of which were found to meet the discrimination criteria. Third, as a result of the construct validity analysis of the Korean CAPL-2 questionnaire scale, it was found that both the criteria for determining concentrated validity and discriminant validity were satisfied.&#x0D; Conclusions Based on the results of this study, the Korean CAPL-2 questionnaire scale is expected to be used as a useful tool for understanding the level of motivation and confidence within physical literacy of elementary school students in Korea.

Magnetic resonance imaging of anal cancer: tumor characteristics and early prediction of treatment outcome

PurposeTo analyze tumor characteristics derived from pelvic magnetic resonance imaging (MRI) of patients with squamous cell carcinoma of the anus (SCCA) before and during chemoradiotherapy (CRT), and to compare the changes in these characteristics between scans of responders vs. nonresponders to CRT.MethodsWe included 52 patients with a pelvic 3T MRI scan prior to CRT (baseline scan); 39 of these patients received an additional scan during week 2 of CRT (second scan). Volume, diameter, extramural tumor depth (EMTD), and external anal sphincter infiltration (EASI) of the tumor were assessed. Mean, kurtosis, skewness, standard deviation (SD), and entropy values were extracted from apparent diffusion coefficient (ADC) histograms. The main outcome was locoregional treatment failure. Correlations were evaluated with Wilcoxon’s signed rank-sum test and Pearson’s correlation coefficient, quantile regression, univariate logistic regression, and area under the ROC curve (AUC) analyses.ResultsIn isolated analyses of the baseline and second MRI scans, none of the characteristics were associated with outcome. Comparison between the scans showed significant changes in several characteristics: volume, diameter, EMTD, and ADC skewness decreased in the second scan, although the mean ADC increased. Small decreases in volume and diameter were associated with treatment failure, and these variables had the highest AUC values (0.73 and 0.76, respectively) among the analyzed characteristics.ConclusionChanges in tumor volume and diameter in an early scan during CRT could represent easily assessable imaging-based biomarkers to eliminate the need for analysis of more complex MRI characteristics.

The association between COVID-19 preventive strategies, virtual reality exercise, use of fitness apps, physical, and psychological health: testing a structural equation moderation model.

Directly or indirectly, individual psychosocial characteristics, motivation, and health consciousness factors help to maintain physical and psychological health through maintaining physical activity. In the current study, we investigated how fitness apps moderate the links among COVID-19 preventive strategies, virtual reality exercise, physical health, and psychological health in Chinese society. A nationwide online survey across China was conducted under a snowball sampling design from February to June 2022. A total of 3,000 questionnaires were distributed across China via online platforms. A total of 2,795 complete detailed replies were included in the final analysis. Structural equation modeling techniques were employed to analyze the collected data through Smart-PLS 3.0. It has been statically proved that all the scales used in this inquiry to determine the mean scores, standard deviation, excess kurtosis, and skewness values were reliable and produced satisfactory results. The overall results (H1: β = 0.385, t = 15.699, p = 0.000; H2: β = 0.159, t = 7.405, p = 0.000; H3: β = 0.122, t = 5.435, p = 0.000; H4: β = 0.143, t = 6.493, p = 0.000; H5: β = 0.157, t = 6.444, p = 0.000; H6: β = 0.184, t = 9.071, p = 0.000; H7: β = 0.192, t = 9.319, p = 0.000; H8: β = 0.235, t = 11.899, p = 0.000; H9: β = -0.114, t = 4.872, p = 0.000; H10: β = 0.042, t = 2.872, p = 0.004; H11: β = 0.041, t = 2.699, p = 0.007) supported our hypothetical model and explained that using fitness apps and virtual reality exercise benefits physical and psychological health. The fitness app's primary purpose during and after the pandemic is to motivate users to keep up with their regular at-home workouts. Exercise and active living are helpful in the prevention of risk factors associated with physical inactivity.

Prediction and Analysis of Chlorophyll-a Concentration in the Western Waters of Hong Kong Based on BP Neural Network

The Chlorophyll-a (Chl-a) concentration is an important indicator of water environmental conditions; thus, the simultaneous monitoring of large-area water bodies can be realized through the remote sensing-based retrieval of Chl-a concentrations. Together with hyperspectral remote sensing data, a BP neural network model was used to invert chlorophyll-a concentration, with remote sensing reflectance as the input factor. Given the presence of many bands in the hyperspectral data, selecting an appropriate band reflectance as the input factor is crucial to improving inversion accuracy. In this study, a Pearson correlation analysis method was proposed to select bands. A normality test was performed on the reflectance of each band of the Zhuhai-1 hyperspectral remote sensing data, and the significance index was p &lt; 0.05. The absolute kurtosis value was less than 10, and the absolute skewness value was less than 3, indicating that the Pearson method was applicable. Pearson correlation analysis was utilised to calculate the correlation coefficient between the reflectance data and chlorophyll-a concentration. Five reflectance data with high correlation were selected as the input factors, and chlorophyll-a concentration was adopted as the output factor. An error backpropagation network model was constructed to predict chlorophyll-a concentration, and a Garson function was added to clarify the connection weights of the input factors in the model construction process. Model 12 was determined as the optimal model on the basis of the criteria of the coefficient of determination, the average relative variance, and the minimum mean square error. The chlorophyll-a concentration was predicted for July and November 2020 in the study area, and the results showed that the predicted values had a small error compared with the measured values. The root-mean-square error and mean relative error of the chlorophyll-a concentration predicted and measured values were 2.12 μg/L and 9.66%, respectively. Significant spatial differences in the Chl-a concentration were observed in the study area due to the influence of islands and land; the Chl-a concentration in July was generally higher than that in November. The results of these studies provide a reference for monitoring the water environment in the study area.

Pretreatment CT Texture Parameters as Predictive Biomarkers of Progression-Free Survival in Follicular Lymphoma Treated with Immunochemotherapy and Rituximab Maintenance.

The purpose of this study was to determine whether texture analysis features present on pretreatment unenhanced computed tomography (CT) images, derived from 18F-fluorodeoxyglucose positron emission/computed tomography (18-FDG PET/CT), can predict progression-free survival (PFS), progression-free survival at 24 months (PFS 24), time to next treatment (TTNT), and overall survival in patients with high-tumor-burden follicular lymphoma treated with immunochemotherapy and rituximab maintenance. Seventy-two patients with follicular lymphoma were retrospectively included. Texture analysis was performed on unenhanced CT images extracted from 18-FDG PET/CT examinations that were obtained within one month before treatment. Skewness at a fine texture scale (SSF = 2) was an independent predictor of PFS (hazard ratio = 3.72 (95% CI: 1.15, 12.11), p = 0.028), PFS 24 (hazard ratio = 13.38; 95% CI: 1.29, 138.13; p = 0.029), and TTNT (hazard ratio = 5.11; 95% CI: 1.18, 22.13; p = 0.029). Skewness values above -0.015 at SSF = 2 were significantly associated with lower PFS, PFS 24, and TTNT. Kurtosis without filtration was an independent predictor of PFS (SSF = 0; HR = 1.22 (95% CI: 1.04, 1.44), p = 0.013), and TTNT (SSF = 0; hazard ratio = 1.23; 95% CI: 1.04, 1.46; p = 0.013). This study shows that pretreatment unenhanced CT texture analysis-derived tumor skewness and kurtosis may be used as predictive biomarkers of PFS and TTNT in patients with high-tumor-burden follicular lymphoma treated with immunochemotherapy and rituximab maintenance.

Investigation of the Relationship between the Life Studies Lesson Attitudes and Critical Thinking Tendencies of Primary School 3rd-Grade Students

The purpose of this study is to determine the level of relationship between the attitudes of 3rd-grade primary school students toward Life Studies lessons and their critical thinking tendencies. The correlational survey model, which is one of the quantitative research methods, was used in the research. The sample of the study consists of 401 "3rd-grade students" in the academic year 2021-2022. The study group was selected using the convenience sampling technique. "Life science lesson and students' attitudes scale" and "Critical thinking tendency scale for primary school students" were used to collect research data. The data obtained from the scales were analyzed using SPSS 22.00 statistical software. Normality distributions were examined to determine the test techniques to analyze the data. For this purpose, Kolmogrov-Smirnov, histogram graph, skewness, and kurtosis values were examined. As a result of the research, it was observed that the critical thinking tendencies of the 3rd-grade primary school students were higher than the attitudes of the Life Studies lesson and there was a low level, positive and significant relationship between them.Keywords: Critical Thinking, Life Studies, Primary School.

Behavioral Risk Measurement: Empirical Evidence From NYSE

This study aims to create a risk measure based on systematic investor behavior. For this purpose, as an alternative to the classical risk measure, volatility, the empirical validity of the downside risk measure, which includes skewness and kurtosis values, was tested. Standard deviation, skewness, and kurtosis differences are used to explain the returns of portfolios created using data from stocks listed on the New York Stock Exchange (NYSE) between 1982 and 2020 depending on different risk concepts. Risk definitions are based on the previous period's skewness and kurtosis coefficients of stock returns. Based on the determined measures, stocks are classified according to their risk level. The relationship between returns and risk measures was examined by regression analysis. According to the results, negative skewness did not provide a higher return than positive skewness. In addition, a higher kurtosis value did not provide higher returns than a lower kurtosis value. As a result, the concept of risk, which represents the loss of the investor, emerges as a result of irrational systematic investor behavior and can be modeled with the skewness coefficient of the return distribution. However, taking a risk in this sense does not promise a reward.

Does Emotional Intelligence Affect Mental Toughness in Physically Disabled Athletes?

The aim of this research is to determine the determinative role of the emotional intelligence sub-dimensions (Assessing others emotions, evaluating their own emotions, regulating emotions, using social skills, use of emotion) in determining the levels of mental toughness of the athletes with disabilities. A total of 261 athletes from 165 disabled athletes (wheelchair basketball, amputee football, sitting volleyball, badminton), male (63.2%) (24.40±5.48 years old) and 96 female (36.0%) participated voluntarily. Within the scope of the research, information about socio-demographic variables was collected by the personal information form created by the researchers. To reach the purpose of the research; The Sport Mental Toughness Questionnaire made by Altıntaş and Bayar (2015) and the Emotional Intelligence Inventory in Sport adapted to Turkish by Adiloğulları and Görgülü (2015) were used. In the analysis of the data, firstly, when the skewness and kurtosis values for the normality assumptions were examined, it was determined that the distribution was normal. In this direction correlation analysis to determine the relationship between variables, stepwise regression analysis was used to determine the power of independent variables in predicting dependent variables. According to the findings obtained as a result of the research, it has been determined that the emotional intelligence levels of the athletes are important determinants of the mental toughness levels, and the analysis completed in three stages explains 56% of the variance.

SEQUENCE OF VALLEY DEVELOPMENT OF ALAKNANDA AND ITS TRIBUTATIES &amp; QUATERNARY SEDIMENTATION, GARHWAL HIMALAYA, PARTS OF CHAMOLI TEHRI UTTAKASHI &amp; PAURI UTTAR PRADESH (UTTRARKHAND STATE ) INDIA

SEQUENCE OF VALLEY DEVELOPMENT OF ALAKNANDA AND ITS TRIBUTATIES &amp; QUATERNARY SEDIMENTATION, GARHWAL HIMALAYA, PARTS OF CHAMOLI TEHRI UTTAKASHI &amp; PAURI UTTAR PRADESH (UTTRARKHAND STATE ) INDIA

Spatial distribution prediction for the ground water quality in Mosul City (Iraq) using variogram equations

The GIS-aided spatial interpolation was applied on collected groundwater data to predict selected parameters (i.e., pH, electrical conductivity, and temperature) for the selected water wells distributed over Mosul City in Iraq. A descriptive statistical analysis was conducted on collected samples to explore the statistical indices. The skewness test was also employed to test the distribution of data sets around their mean values. The natural logarithms function achieved least skewness values and thus was applied to transfer data sets in order to adjust normality of the data sets distribution. Among all applied semivariogram models, the J-Bessel semivariogram model was optimal in terms of root mean square error (RMSE) values. The average standard errors were 0.2217, 740.5, and 1.209 for pH, EC, and temperature, respectively.