Kolmogorov-Smirnov Research Articles

Hyaluronan-Mediated Motility Receptor (HMMR) Overexpression Is Correlated with Poor Survival in Patients with B-ALL

Acute lymphoblastic leukemia (ALL) is a malignant neoplasm with the highest incidence in the pediatric population. Although the 5-year overall survival is greater than 85%, in emerging countries such as Mexico, the mortality rate is high. In Mexico, B-ALL is the most common type of childhood cancer; different characteristics suggest the presence of the disease; however, the prognosis is dependent on clinical and laboratory features, and no adverse prognostic molecular marker for B-ALL has yet been identified. The present research aimed to identify the prognostic value of HMMR expression in pediatric patients with B-ALL. The differential expression profile of B-ALL cells was determined via in silico analysis, and HMMR expression was subsequently measured via qRT–PCR and immunocytochemistry. The results were statistically analyzed via the ROUT test, Kolmogorov–Smirnov Z test, and Mann–Whitney U test. ROC curves and the Youden index were constructed, and Kaplan–Meier curves were plotted. We found that HMMR expression was increased in B-ALL patients (p < 0.0001). We observed that high expression was related to poor prognosis (p < 0.05). We observed that high expression was related to poor prognosis (p < 0.05). The increase in HMMR expression could be a potential early molecular prognostic marker and/or a new target in childhood B-ALL patients.

Decoding systemic risks across commodities and emerging market stock markets

This study explores correlations and risk spillovers, essential concepts for financial risk management, among commodities (crude oil, gold, and a global commodities index) and emerging stock markets. Using the Asymmetric Dynamic Conditional Correlation–Conditional Value-at-Risk (ADCC-CoVaR) model and a bootstrapped Kolmogorov–Smirnov (KS) test, we analyze the period from December 30, 2005, to February 28, 2024, examining correlations, downside and upside risk spillovers, and highlighting the effects of major events such as the global financial crisis of 2008, the COVID-19 pandemic, and the Russia-Ukraine war. The results show heightened correlations during crises and significant risk spillovers across market pairs, with downside risks often outweighing upside risks. Gold displays minimal risk spillover, highlighting its unique role as a haven asset. We find that spillovers between gold, global commodities, and stocks increased during the pandemic and the Russia-Ukraine conflict, while those involving crude oil remained stable. These findings provide valuable guidance for portfolio managers in navigating volatile markets.

Imagined Intimacy: The Link Between Attachment Styles and Parasocial Relationship of Senior High School Students

This present study was designed to investigate how different attachment styles influence individuals' susceptibility to parasocial experiences, focusing on senior high school students through questionnaires assessing secure, fearful, preoccupied, and dismissing attachment styles. 300 senior high school students, 11 and 12, participated in this study from the University in the Mindanao Region of the Philippines. The Kolmogorov-Smirnov test showed that the data were normally distributed (D =.035, p-value =.200). The levels of both variables were described using means and standard deviations. The study found low levels of Secure Attachment Style among students (X=2.23, SD=.337), indicating difficulties in emotional connections. A high level of Fearful Attachment Style was linked to anxiety and avoidance (X=3.56, SD= .419), while Preoccupied Attachment Style (X=3.86, SD=.389), and a high level of Dismissing Attachment Style (X=3.70, SD=.409). High levels of parasocial relationships were noted (X=3.54, SD= .51). Parasocial relationships and Secure Attachment Style had a weakly negative link (r = -.143, p =.013). Conversely, there were extremely minor positive connections between dismissing attachment styles (r =.095, p =.002) and preoccupied attachment styles (r =.002, p = 0.023). There was no significant link with Fearful Attachment Style (r = -0.025, p = 0.661). All things considered, our results point to a somewhat favourable correlation between parasocial relationships and attachment type (r = 0.494, p = 0.05). According to linear regression, Secure Attachment Styles have a negative correlation (B = -.189, p =.009) with parasocial connections, while Dismissing Attachment Styles have a positive correlation (B =.117, p =.004).

Transformational leadership model as a strategy to optimize the work environment for teachers in educational institutions

The transformational leadership model as a strategy to optimize the work environment for teachers in educational institutions proposes a transformational approach to strengthen the workplace atmosphere among educators. Using a quantitative methodology and a non-experimental cross-sectional design, the research involved 65 participants, including teachers and administrative staff, who responded to surveys with 64 questions. The data analysis, conducted using SPSS software and validated through the Kolmogorov-Smirnov test (p < 0.001), confirmed that implementing a transformational leadership model significantly improves the work environment. The results emphasize that this leadership approach, based on motivation and personal development, positively impacts collaboration and productivity within the educational institution, highlighting its potential to optimize the organizational climate in academic environments.

Application of Statistical Methods for the Characterization of Radon Distribution in Indoor Environments: A Case Study in Lima, Peru

This study evaluates the effectiveness of advanced statistical and geospatial methods for analyzing radon concentration distributions in indoor environments, using the district of San Martín de Porres, Lima, Peru, as a case study. Radon levels were monitored using LR-115 nuclear track detectors over three distinct measurement periods between 2015 and 2016, with 86 households participating. Detectors were randomly placed in various rooms within each household. Normality tests (Shapiro–Wilk, Anderson–Darling, and Kolmogorov–Smirnov) were applied to assess the fit of radon concentrations to a log-normal distribution. Additionally, analysis of variance (ANOVA) was used to evaluate the influence of environmental and structural factors on radon variability. Non-normally distributed data were normalized using a Box–Cox transformation to improve statistical assumptions, enabling subsequent geostatistical analyses. Geospatial interpolation methods, specifically Inverse Distance Weighting (IDW) and Kriging, were employed to map radon concentrations. The results revealed significant temporal variability in radon concentrations, with geometric means of 146.4 Bq·m−3, 162.3 Bq·m−3, and 150.8 Bq·m−3, respectively, across the three periods. Up to 9.5% of the monitored households recorded radon levels exceeding the safety threshold of 200 Bq·m−3. Among the interpolation methods, Kriging provided a more accurate spatial representation of radon concentration variability compared to IDW, allowing for the precise identification of high-risk areas. This study provides a framework for using advanced statistical and geospatial techniques in environmental risk assessment.

APAKAH BEBAN KERJA MENTAL BERHUBUNGAN DENGAN TINGKAT KECEMASAN PADA KARYAWAN BANDARA?

Anxiety was the anticipation of future danger accompanied by feelings of dysphoria and somatic symptoms. Anxiety often occured in employees within the early adults (ages 26-35). Risk factors of anxiety in employees included genetics, social and family environmental factors, and mental workload. The impact of mental workload on employees could affect mental health, specifically the level of anxiety, that could implicate the job performance. The aim of this study was to assess the relationship between gender, age, and mental workload with the anxiety levels of airport employees. The design of the study was observational analytic cross-sectional approach. A sample size of 125 subjects were obtained through cluster random sampling. Primary data was collected using the HARS and NASA-TLX questionnaires. Data were analyzed with SPSS using the Kolmogorov-Smirnov and Kendall's Tau tests. There were 69 male employees and 53 individuals were in the early adulthood (26-35 years). For mental workload, 51 employees had a slightly high workload and 47 employees had severe anxiety.The bivariate analysis indicated that there was no relationship between gender and anxiety levels (p=0.709) as well as age and anxiety levels (p=0.142). However, there was a relationship between mental workload and anxiety levels (p=0.005). Mental workload is related with anxiety levels in airport workers.

HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION

Water is a natural resource important for life and daily activities. Water distributed by the Regional Drinking Water Company (PDAM) should include a coagulation process using liquid aluminum sulfate as a coagulant before it can be consumed. Therefore, this research aims to predict the need for liquid aluminum sulfate in PDAM from 2023 to 2024 using Holt-Winter's method. It also aims to evaluate the optimum liquid aluminum sulfate chemical inventory policy using Q probabilistic inventory model with Normal and erlang probabilistic distributions in PDAM. The data was obtained from Tirta Musi PDAM in Palembang City, Indonesia. The results of forecasting liquid aluminum sulfate demand level data with the Holt-Winter multiplicative method provide the smallest MAPE value. The erlang probability distribution assumption has been met through the Kolmogorov Smirnov test method. The erlang probabilistic inventory model provides a more optimal policy solution than the normal probabilistic inventory model, with minimum total cost and higher service level.

Investigation of the Effects of Thermal Cycling and Surface Treatments on Interim Resin Materials Produced with Additive Manufacturing

This study aimed to compare the impact of thermal cycling on the flexural strength (σfs) of 3-dimensional (3D) printer resins and polymethyl methacrylate (PMMA). It also aimed to evaluate different surface treatment protocols and surface sealant applications on the surface roughness (Ra) and surface hardness (VHN) of the resins used. Rectangular (25�2�2 mm) and disc (Ø10�2-mm) specimens were fabricated from auto-polymerized PMMA, and 3D-printed resins were tested for mechanical properties (ISO 10477) using thermal cycling (n=10). Disc specimens were separated into three groups (n=10) based on the surface treatments: conventional sanding (C), disk polishing (P), and surface sealant coating (O). Ra and VHN values were statistically analyzed with the Kolmogorov Smirnov, Shapiro Wilk, Independent Samples t-test, Mann-Whitney test, one-way ANOVA test and Kruskal Wallis test (α =.05). A significant main effect was found on the flexural strength analysis for each of the two factors: thermal cycling procedure (p[0.001) and materials (p 0.001). A significant main effect was found on the surface roughness and hardness analysis for each of the two factors: surface treatment protocols (p[0.001) and materials (p[0.001). Based on the results; interim materials produced with 3D-printed resins have better mechanical properties than conventionally polymerized materials. Coated materials had lower surface roughness values than polished ones, and adding a surface sealant agent increased their hardness significantly.

Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator

To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related discomfort and risks. Data from 655 patients who underwent transperineal prostate biopsy at the First Affiliated Hospital of Wannan Medical College from July 2021 to January 2023 were collected and analyzed. After applying the Synthetic Minority Over-sampling TEchnique class balancing on the training set, multiple machine learning models were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection to identify the significant variables. The best-performing model was selected and evaluated through tenfold cross-validation to ensure interpretability. Finally, the performance was assessed using the test set data for validation. The age, prostate-specific antigen mass ratio (PSAMR), Prostate Imaging–Reporting and Data System, and prostate volume were selected as the variables for model construction based on the LASSO regression. The receiver operating characteristic (ROC) results for multiple models in the validation set were as follows: XGBoost: 0.93 (0.88–0.97); logistic: 0.89 (0.83–0.95); LightGBM: 0.87 (0.80–0.93); AdaBoost: 0.90 (0.85–0.96); GNB: 0.88 (0.82–0.95); CNB: 0.79 (0.71–0.87); MLP: 0.78 (0.69–0.86); and Support Vector Machine: 0.81 (0.73–0.89). XGBoost was selected as the best model and reconstructed with tenfold cross-validation on the training data, resulting in the following ROC scores: training set 0.995 (0.991–0.999), validation set 0.945 (0.885–0.997 ), and test set 0.920 (0.868–0.972). The Kolmogorov–Smirnov curve, calibration curve and learning curve yielded positive results; The decision curve demonstrates that patients with threshold probabilities ranging from 10 to 95% can benefit from this model. We developed an XGBoost machine learning model based on the PSAMR indicator and interpreted it using the SHapley Additive exPlanations method. The model offered a high-performance non-invasive technique to diagnose prostate cancer in patients with PSA levels < 20 ng/ml.

Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework

This study aims to develop an efficient model to predict the arrears behavior of electricity users by integrating multi-scale feature learning with a backpropagation (BP) neural network. The goal is to provide accurate early warning systems and enhanced risk management tools for power companies. The BP neural network algorithm adjusts weights to minimize prediction errors, while multi-scale feature learning captures the diversity and regularity of user behavior by extracting data from various time dimensions, such as daily, weekly, and monthly intervals. First, electricity usage and weather data from the UMass Smart Dataset are preprocessed, including steps such as data cleaning, standardization, and normalization. Next, features are extracted across three time scales—daily, weekly, and monthly. These features are then input into the BP neural network model using the multi-scale feature learning method. A hierarchical neural network structure is designed to address the characteristics of different scales in distinct layers. Key model parameters are optimized, and a sensitivity analysis is conducted. The experimental results demonstrate that the BP neural network model incorporating multi-scale features outperforms traditional BP neural network models and other control models in several evaluation metrics. Specifically, the Gini coefficient is 0.55, the Kolmogorov-Smirnov statistic is 0.60, the Matthews correlation coefficient is 0.45, and specificity is 0.82. These results indicate that the proposed method offers significant improvements in capturing user behavior patterns and enhancing prediction accuracy. The study concludes that the effective fusion of multi-scale features not only enhances the model’s prediction performance but also strengthens its generalization ability. This method provides an advanced risk management tool for power companies, helping to increase the operational efficiency of smart grids and encouraging further research toward greater intelligence in the field.

Unveiling the Texture Secrets of Morchella Germplasm: Advanced Grading and Quality Assessment Through Texture Profile Analysis (TPA).

Morchella is an edible mushroom with medical applciations. To explore the correlation between the texture indices of Morchella and to establish a sensory quality evaluation system, the texture quality characteristics of 214 Morchella germplasm resources from our country were analyzed via the Texture Profile Analysis (TPA) method on a texture analyzer. The research revealed significant differences in the texture quality characteristics of both the pileus and stipe among Morchella populations. After the Kolmogorov-Smirnov test, the six texture characteristics were seen to conform to a normal distribution. According to the correlation analysis, there was a significant correlation between the texture characteristics of the pileus, and a significant positive correlation between the hardness and the gumminess of the stipe (correlation coefficient of 0.96). Additionally, the hardness was negatively correlated with cohesiveness and resilience, with correlation coefficients of -0.51 and -0.38. Variation analysis indicated abundant genetic variation in each characteristic. Furthermore, the coefficient of variation for the characteristics of Morchella sextalata was higher than those of other species. Principal component analysis simplified the texture evaluation indices of Morchella pileus into a palatable factor and cohesive factor, and arranged the texture evaluation indexes of Morchella stipe into toughness-hardness factor and cohesive factor. Through comprehensive evaluation and cluster analysis, 10 Morchella strains were selected for subsequent use as breeding or cultivation materials. By comparing three different methods, the 'probability grading method' was determined to be the most suitable evaluation method for the texture quality characteristics of Morchella. The research results established a texture evaluation system for Morchella, offering a reference for selecting and cultivating breeds with superior texture qualities.

Propofol Priming for Enhancing Induction Safety in Hypertensive Patients: A Prospective Double-blind Randomised Controlled Trial

Introduction: Propofol is popular for inducing general anaesthesia, but it has drawbacks such as hypotension and bradycardia in a dose-dependent manner, especially in hypertensive patients. Reducing the total dose of Propofol using the priming principle has proven to be effective; however, it has not been studied in high-risk hypertensive patients. Therefore, the current study was planned. Aim: To evaluate the effects of priming on Propofol induction in controlled hypertensive patients, with objectives to assess haemodynamic parameters, total dose, and sideeffects. Materials and Methods: This prospective, comparative, double-blind randomised controlled trail was performed at the Department of Anaesthesiology, Pt. Bhagwat Dayal Sharma (B.D.) Postgraduate Institute of Medical Sciences (PGIMS) Rohtak, Haryana, India, from April 2023 to April 2024. A total of 60 patients scheduled for elective surgery under general anaesthesia with controlled hypertension were randomly assigned to either Group 1 (study group, n=30), where Propofol priming was used, or Group 2 (control group, n=30). Demographics, total Propofol dose, haemodynamic parameters {Heart Rate (HR), Systolic Blood Pressure (SBP), Mean Arterial Pressure (MAP)}, and adverse events were evaluated using International Bussiness Machine (IBM) Statistical Package of Social Sciences (SPSS) version 25.0. The Kolmogorov-Smirnov test was used for normalisation, and the Mann’s-Whitney U test, Independent t-test, and Chi-square test were used for data analysis. Results: In Group 1 (study), the mean age was 49.36±9.42 years, while in Group 2 (control), it was 49.36±9.19 years (p=0.91). A lesser dose of Propofol was needed in the study group (Group 1) (90.07±19.73 mg) compared to the control group (Group 2) (120.00±21.81 mg) (p=0.001). Haemodynamic alterations were more pronounced in the controls compared to the study group. After induction, a significant fall in MAP was observed in the controls compared to the study group (67.63±5.86 mmHg vs. 90.63±4.33 mmHg) (p=0.001). Adverse effects, such as pain at the injection site, were reported in one patient (n=1) in Group 2. Conclusion: The priming principle significantly reduces the total Propofol dose and leads to more stable haemodynamics during general anaesthesia induction in controlled hypertensive patients. Priming with Propofol is advised for patients with hypertension when inducing general anaesthesia.

Methodical Approach to Selecting the Appropriate Distribution for Reliability Analysis: Automotive Application

In this study, we propose a methodical approach to selecting an appropriate statistical distribution for reliability analysis. In this approach, we have defined a methodology for testing reliability distributions based on the Kolmogorov Smirnov K-S test for MTBF Data collected from Self-Diagnostic of a sample of 50 critical components part of a complex automotive system. Finally, we proposed two solutions: the first involves migrating from one distribution to another according to the intervals, and the second allows for the selection of the distribution that is representative over a maximum number of intervals. These strategies were developed from the analysis of results after application of the K-S test on the distributions tested. This approach will contribute. to the reliability analysis of complex systems. As a result, in improving the models used to analyze complex systems behavioral analogies such as Petri nets or Markov chains.

Effects of fibroblast growth factor 21 serum level on clinicopathological findings in papillary thyroid carcinoma.

This research examined the connection between circulating FGF21 and clinicopathological findings in papillary thyroid carcinoma. This analytical cross-sectional research was conducted on patients with papillary thyroid cancer at the Seyyed Shirazi Endocrinology Clinic in Gorgan, Iran. Laboratory data, including demographics, ultrasonography and pathology reports, and FGF21 levels, were collected. The data was analyzed with SPSS 25. Normal distribution was evaluated by using Kolmogorov-Smirnov and Shapiro-Wilk tests. Group differences were evaluated with Chi-square, independent sample t-test and Mann-Whitney U tests. A p-value less than 0.05 was considered significant. In this research, 83% of patients were female, and the mean±SD age was 42.51±13.28 years old. The mean±SD and FGF21 concentrations in 49 patients were 716.41±458.7, the median was 489 pg/ml, and 24 (49%) patients were in the high FGF21 group. There was no statistically significant relation between FGF21 level and age (P=0.95), sex (P=>0.99), tumor size (P=0.68), tumor stage (P=>0.99), lymphadenopathy (P=>0.99), lymph node metastasis (P=0.24), triglycerides (P=0.93), total cholesterol (P=0.47), LDL (P=0.08), and HDL (P=0.08). However, FGF21 levels were significantly associated with fasting blood glucose (P=0.03), body mass index (BMI) (P=<0.0001), capsular invasion (P=0.001), lymphovascular involvement (P=0.0001) and Thyroid Imaging Reporting and Data System (TIRADS) score (P=0.02). In addition, high levels of FGF21 were found to be 78.95% sensitive and 70% specific for capsular invasion. Our study demonstrated that FGF21 is associated with more severe papillary thyroid cancer clinicopathological features such as capsular invasion, lymphovascular involvement, TIRADS score, and BMI.

Modeling urban pollutant wash-off processes with ecological memory.

Urbanization increases the extent of impervious surfaces, runoff, sediment, and nutrient loadings downstream, leading to the deterioration of urban surface waters. During pollutant wash-off from urban surfaces, the peak concentration of pollutants typically occurs after the rainfall peak. However, current urban wash-off models do not consider this time delay, assuming that the effect of rainfall on the wash-off process is immediate. Ecological memory (EM) is defined as the capacity of past states or experiences to influence the present or future ecological responses of a community ecosystem. In this study, ecological memory was calculated to reflect the lagging impact of rainfall on the wash-off process. Incorporating ecological memory into the original wash-off model improved its performance across all pollutant types and rainfall conditions, with the adjusted R-squared value increasing from -0.01-0.61 to -0.08-0.83. Among the factors impacting ecological memory, rainfall intensity significantly affected the distributions of ecological memory (p<0.05 according to the Kolmogorov-Smirnov test). The first flush phenomenon, which involves a larger concentration or mass of pollutants in the initial portion of a storm event compared to the rest, showed no significant difference in the distributions of ecological memory between rain events with and without this phenomenon. The improved urban wash-off model can be applied for real-time simulation of urban pollutants and help develop site-specific measures for reducing urban nonpoint source pollution.

Most High-density Exoplanets Are Unlikely to Be Remnant Giant Planet's Cores

Some exoplanets have much higher densities than expected from stellar abundances of planet-forming elements. There are two theories—metal-rich formation hypothesis and naked core hypothesis—that explain how formation and evolution can alter the compositions and structures of rocky planets to diverge from their primordial building blocks. Here we revisit the naked core hypothesis, which states that high-density planets are remnant cores of giant planets that remain in a fossil-compressed state, even after envelope loss. Using a planetary interior model and assuming energy-limited atmospheric escape, we show that a large fraction, if not all, of the iron–silicate core of a giant planet is molten during the planet's early evolution. Upon envelope loss, the molten part of the planets can rapidly rebound owing to low viscosity, resulting in a decrease in radius by at most 0.06%, if they had hydrogen/helium envelopes, or by at most 7%, if they had H2O envelopes, compared to self-compressed counterparts with the same core mass fraction. Based on our findings, we reject the hypothesis that all high-density exoplanets are naked cores with Kolmogorov–Smirnov p-value ≪0.05 for both envelope compositions. We find that some high-density exoplanets can still possibly be naked cores, but the probabilities are lower than ∼1/2 and ∼1/3 for the ice giant and gas giant scenario, respectively, in 95% of the cases. We conclude that most high-density exoplanets are unlikely to be remnant giant planet cores.

RELATIONSHIP BETWEEN THE HABIT OF BRINGING LUNCH AND ENERGY INTAKE WITH NUTRITIONAL STATUS IN ADOLESCENT GIRLS AT SMAN 1 CIKARANG SELATAN

Introduction: School age is a critical stage where energy and nutrient needs must be met, as adolescents are in a phase of growth and development. Therefore, it is essential to ensure high-quality food that can meet the nutritional needs of adolescents while they are at school. The aim of this study is to determine the relationship between the habit of bringing lunch and energy intake with the nutritional status of female adolescents. Methods: This study used a quantitative approach with a cross-sectional design. The population in this study were adolescent female students at SMAN 1 Cikarang Selatan. The sample of 50 people was taken by purposive sampling. Data collection was conducted using a food consumption assessment questionnaire, namely the 24-hour food recall, along with a body weight scale, microtoise, and metline. Kolmogorov Smirnov test was used to test normality, and Pearson test to see the relationship between variables. Results: Based on statistical tests there is a relationship between the habit of bringing lunch with a significant nutritional status based on Z-Score IMT / U (p-value = 0.002), there is a relationship between the habit of bringing lunch withnutritional status based on %LILA (p-value 0.000) and there is no relationship between energy intake with nutritional status based on ZScore IMT/U (p-value 0.442), and no association was found between energy intake and nutritional status based on %LILA (p-value=0.570). Conclusion: There is a significant relationship between the habit of bringing lunch according to Z-Score IMT/U and %LILA.

Assessment of Nutrition Knowledge in Pregnant Women of Lahore: An Interview Based Study at Major Hospitals of Lahore During Prenatal Visits

Background: The intentions of the following study were to assess women knowledge regarding dietary practices during pregnancy. The study expresses the nutrition related knowledge of pregnant females and its correlation with associated factors of these women. The study also shows the sources of dietary guidance for these women during pregnancy. Method: The study members visited different hospitals of Lahore, interviewed pregnant women and filled questionnaire regarding their knowledge of dietary practices during pregnancy. The statistical tests applied were frequency, percentage, mean, standard deviation, Regression, Kolmogorov-Smirnov test and Spearman’s correlation. Results: 364 questionnaires were finished and analysed using software. Pregnancy related nutrition knowledge was positively correlated with level of education (rs= 0.46, p&lt;0.05) and monthly income (rs=0.27, p&lt;0.05). Only 4.3% of women attained pregnancy scores related to nutrition knowledge above 50%. They mostly get information from their mothers and doctors. Majority of the women recommended increasing intake of supplies from all food groups and fluid. The result indicated that nutritional behaviour of women was characterized by many ill practices. Conclusion: Women interviewed for this research had restricted nutrition knowledge and proper nutrition guidelines were not provided to pregnant women at health care facilities. Women followed insufficient food routines in pregnancies that were mostly directed by mothers of women. The diet of a female during pregnancy has a direct effect on fitness outcomes of mother and child. Many women lacked this information and thus ended with micro-nutrient deficiencies. So there is an alarming need to train women to enhance their knowledge for appropriate dietary patterns to avoid severe outcomes in the form of compromised maternal-child health

An Effectiveness Test Combination of Ethanol Extracts of Buas-buas Leaves (Premna serratifolia L.) and Sappan Wood (Caesalpinia sappan L.) as Topical Antiinflammatory Agent in Male White Rats (Rattus novergicus)

Background: Inflammation is the reaction of the immune system to tissue damage resulting from physical injury, harmful chemicals, or microbial agents. Steroid and non-steroid drugs are commonly used to treat inflammation, but long-term use can result in side effects, such as hormonal disorders and gastric ulcers. Buas-buas leaves and sappan wood has potential as traditional medicines, and based on empirical evidence, they utilize both plants as anti-inflammatory, antibacterial, antioxidant, antiallergic, and antiarthritic agents, as well as for the treatment of cardiovascular disorders, cough, and leprosy. Objective: This study aimed to evaluate the effect of combining 96% ethanol extracts from buas-buas leaves and sappan wood to deliver topical anti-inflammatory benefits. Methods: This research was experimental, using thirty male rats divided into six treatment groups: a negative control group with 2% carrageenan, Biocream® control group, a positive control group with Hydrocortisone Acetate, and three treatment groups receiving a combination of ethanol extracts from buas-buas leaves and sappan wood at concentrations of 1.67%, 2.5%, and 3.75%. The test compounds were administered after carrageenan injection. Measurement of skinfold thickness on the backs of the rats was conducted every hour for 6 h using digital calipers, and the difference in skinfold thickness of each rat, AUC value, and percentage of inflammation inhibition was calculated. Data analysis involved the Kolmogorov-Smirnov test and Levene's test to assess normality and homogeneity, respectively, and was subsequently followed by One-way ANOVA and a post-hoc test. Conclusion: The combination of ethanol extracts of Buas-Buas leaves and sappan wood can provide a topical anti-inflammatory effect, with the most effective concentration being 3.75% and an inflammation inhibition percentage of 32.77%.

Motivational Factors Affecting University Students’ Participation in Sports Betting

This study was conducted to determine the motivations for gambling among university students who participate in sports betting. The sample of the research consists of 137 students (mean age 22±54) studying at Ardahan University. The data collection tools used in the study included a personal information form and the “Gambling Motivation Scale” developed by Chantal et al., and adapted to Turkish by Karlı, comprising 28 items assessing motivations for gambling. Statistical analysis of the data was carried out using computer software. The Kolmogorov-Smirnov test indicated that the data were normally distributed. Arithmetic mean (x), frequency (f), Independent Samples t-test for pairwise comparisons, and one-way ANOVA test for comparisons of means across more than two groups were applied to analyze the data. The research findings revealed significant differences in gambling motivation levels among university students based on variables such as the degree of addiction, frequency of betting, and the duration of betting participation.