Correlation Linear Regression Research Articles

Nut consumption, gut microbiota, and body fat distribution: results of a large, community-based population study.

We aimed to investigate the relationships among nut consumption, gut microbiota, and body fat distribution. We studied 2255 Chinese adults in the Lanxi Cohort living in urban areas in Lanxi City, China. Fat distribution was assessed by dual-energy x-ray absorptiometry, and nut consumption was assessed using food frequency questionnaires. 16S ribosomal RNA (rRNA) sequencing was performed on stool samples from 1724 participants. Linear regression and Spearman correlation were used in all analyses. A validation study was performed using 1274 participants in the Lanxi Cohort living in rural areas. Nut consumption was beneficially associated with regional fat accumulation. Gut microbial analysis suggested that a high intake of nuts was associated with greater microbial α diversity. Six genera were found to be associated with nut consumption, and the abundance of genera Anaerobutyricum, Anaerotaenia, and Fusobacterium was significantly associated with fat distribution. Favorable relationships between α diversity and fat distribution were also observed. Similar relationships between gut microbiota and fat distribution were obtained in the validation analysis. We have shown that nut consumption is beneficially associated with body fat distribution and gut microbiota diversity and taxonomy. Furthermore, the microbial features related to high nut intake are associated with a favorable pattern of fat distribution.

Paediatric nurses' perspectives on artificial intelligence applications: A cross-sectional study of concerns, literacy levels and attitudes.

This study aimed to explore the correlation between artificial intelligence (AI) literacy, AI anxiety and AI attitudes among paediatric nurses, as well as identify the influencing factors on paediatric nurses' AI attitudes. A descriptive, correlational and cross-sectional research. This study was conducted between January and February 2024 with 170 nurses actively working in paediatric clinics in Turkey. The data collection tools included the Nurse Information Form, the General Attitudes Towards Artificial Intelligence Scale (GAAIS), the Artificial Intelligence Literacy Scale (AILS) and the Artificial Intelligence Anxiety Scale (AIAS). To determine the associations between the variables, the data was analysed using IBM SPSS 28, which included linear regression and Pearson correlation analysis. The study indicated significant positive correlations between paediatric nurses' age and their AIAS scores (r = .226; p < .01) and significant negative correlations between paediatric nurses' age and their AILS (r = -.192; p < .05) and GAAIS scores (r = -.152; p < .05). The GAAIS was significantly predictive (p < .000) and accounted for 50% of the variation in AIAS and AILS scores. Paediatric nurses' attitudes towards AI significantly predicted AI literacy and AI anxiety. The relationship between the age of the paediatric nurses and the anxiety, AI literacy and attitudes towards AI was demonstrated. Healthcare and educational institutions should create customized training programs and awareness-raising activities for older nurses, as there are noticeable variations in the attitudes of paediatric nurses towards AI based on their age. Providing in-service AI training can help healthcare organizations improve paediatric nurses' attitudes towards AI, increase their AI literacy and reduce their anxiety. This training has the potential to impact their attitudes positively and reduce their anxiety. The study results were critically reported using STROBE criteria. No patient or public contribution.

Estimation of human height using ulnar length in the Muslim community of Golbazar Municipality, Siraha, Nepal

Calculating an individual's height based on bone measurements is critical in identifying unknown bodies, body parts, or skeletal remains. Anthropologists, anatomists, and forensic experts have used a variety of anthropometric approaches to forecast stature from skeletal remains. Although few studies have been conducted to understand ulnar length and height, it has not been conducted in a few ethnic communities of Nepal. This study aimed to analyze the relationship between human height and ulnar length in Muslim communities of Golbazar Municipality, Siraha, Nepal. Two hundred people (male 100 and female 100) aged 20 to 40 years were purposively selected from Golbazaar, Siraha, Nepal. Ulnar length was measured as the distance between the tip of the Olecranon process and the styloid process with the elbow fully flexed. Height was measured from the top of the head to the floor while the participants stood upright in the anatomical position with their heads in the Frankfort plane. Statistical techniques, such as linear regression analysis and correlation coefficients, were used to determine a correlation between ulna length and height. The population's mean ulna length was 26.53 cm (SD = 2.06), and the mean height was 159.59 cm (SD = 9.72). The correlation between ulna length and height was stronger in males (0.46) than in females (0.36). The study established regression equations for height estimation based on ulna length for different age groups, with the strongest correlations found in the 31–35 years age group and weaker ones in the 20–25 years and 26–30 years age groups. The study suggests that ulna length could be a reliable predictor of height, especially when direct measurement is challenging or impossible. However, additional study is required to explore potential differences based on age, ethnicity, and gender and to validate the findings in more extensive and more diverse populations.

Proof-of-concept study: Remote capillary blood collection for hCG analysis in early pregnancy

IntroductionCapillary blood collection, a technique traditionally used in diabetes care, shows promise for many applications including pregnancy monitoring. Serial measurement of serum human Chorionic Gonadotrophin (hCG) is frequently necessary for managing early pregnancy, including molar pregnancy, necessitating multiple visits to a maternity hospital for blood collection by venepuncture. This proof-of-concept study aimed to assess the clinical performance and user acceptability of capillary blood samples collected remotely, as an alternative to venous blood for hCG measurement. MethodsWomen attending the early pregnancy unit who required serum hCG measurement, were invited to participate. Following informed written consent, participants were shown how to collect capillary blood samples using the Mini-Collect® collection device. Matched venous and capillary blood samples were collected in clinic for hCG comparison purposes. Participants were also supplied with a home collection kit in a prepaid envelope. They were asked to perform a finger-prick blood collection at home using the instructions provided and to return the capillary blood sample by post within 24 h of collection, along with a completed user-satisfaction questionnaire. Statistical analysis was performed using Analyse-it® software. ResultsThe study enrolled 71 participants and over a third of these women collected a capillary blood sample at home. The median age of participants was 33 years (range 29–36). Passing-Bablok linear regression (y = -0.037 + 1.04x) and Spearman correlation (r = 0.999, p < 0.0001), demonstrated good agreement and strong correlation between venous and capillary samples, over a broad range of hCG values (1.2 to 224,0000 IU/L). The majority of capillary samples collected remotely (39 %, 27/69) had sufficient blood volume for analysis (74 %, 20/27). Respondents (77 %, 18/25) found the collection device easy to use and expressed willingness to use a future service if available (80 %, 20/25) ConclusionThe study demonstrated excellent agreement between the hCG results obtained from both collection methods, suggesting that capillary blood can serve as a reliable alternative for venous hCG measurement, particularly in clinical settings requiring frequent hCG monitoring. Feedback from the study questionnaire indicates a preference for this type of follow-up among women, indicating potential improvements in compliance for blood based diagnostic tests.

Clinical validation of the novel fluorescent glomerular filtration rate tracer agent relmapirazin (MB-102)

The fluorescent compound relmapirazin has been rationally designed for use in point-of-care measurement of glomerular filtration rate (GFR), with attributes including negligible protein binding, negligible metabolites in vivo, negligible tubular secretion, and excellent chemical and photo stability. Twenty-four nonclinical assays were performed in accordance with FDA requirements yielding negligible toxicology concerns. Here, a clinical study was performed to validate relmapirazin as a GFR tracer in patients by comparison to iohexol. This was evaluated in 120 adults at three clinical sites with eGFR values ranging from normal to Stage 4 chronic kidney disease. Relmapirazin and iohexol were administered intravenously in consecutive boluses to each subject and serial blood samples obtained over the subsequent 12 hours. Plasma concentrations were measured and the corresponding plasma GFR for each agent was determined using a standard two-compartment pharmacokinetic assessment. Urine from each subject was collected for the entire 12-hour study period to measure the amount of administered dose appearing in the urine. A near perfect linear regression correlation was observed between the GFRs measured by these two tracers (r2=0.99). Bland-Altman analysis confirmed agreement between these two measures of GFR (limits of agreement -7.0 to +5.6 mL/min; mean of -0.7 mL/min). The GFR determined by relmapirazin was independent of GFR stratification by chronic kidney disease stage, and importantly by race. The percent of the administered relmapirazin dose recovered in the urine was greater than or equal to that of iohexol with no reported severe adverse events. Thus, relmapirazin may be used as a GFR tracer agent in humans.

Comparing the performance of machine learning models for predicting the compressive strength of concrete

This work aimed to investigate and compare the performance of different machine learning models in predicting the compressive strength of concrete using a data set of 1234 compressive strength values. The predictive variables were selected based on their relevance using the SelectKBest method, resulting in an analysis of eight and six predictive variables. The evaluation was conducted through linear correlation studies via simple linear regression and non-linear correlation studies using support vector regression (SVR), random forest (RF), gradient boosting (GB), and artificial neural networks (ANN). The results showed a coefficient of determination (R2) = 0.897 and a root mean square error (RMSE) = 6.535 MPa for SVR, R2 = 0.885 and RMSE = 5.437 MPa for GB, R2 = 0.868 and RMSE = 5.859 MPa for GB and R2 = 0.894 and RMSE = 5.192 MPa for ANN, all for test set and eight predictor variables. The comparison between the machine learning methods revealed significant differences. For instance, ANN stood out with a higher R2 value, demonstrating its remarkable ability to explain the variability in the data. ANN also showed the lowest RMSE value, indicating notable accuracy in the predictions. Although ANN has demonstrated higher performance, GB shows a closer performance, which no differences from a practical application. The choice between these approaches depends on considerations regarding the balance between explainability and accuracy. While GB provides a more in-depth understanding of the relationship between variables, ANN stands out for the accuracy of its predictions.

Dinamika kinerja guru: Peran krusial supervisi pengawas, kepemimpinan kepala sekolah, dan motivasi kerja guru

Background: This research is motivated by the importance of teacher performance in determining the quality of education. Factors such as supervisory supervision, principal leadership, and teacher work motivation are thought to have a significant contribution to teacher performance. Method: To test this hypothesis, quantitative methods were used with multiple and partial regression approaches. Data was collected from 21 schools and analyzed to determine the extent to which each factor influences teacher performance. In addition, the data collection technique used a questionnaire. The data analysis technique used multiple linear regression and partial correlation. Findings: The research results show that there is a significant positive influence on the contribution of supervisory supervision, principal leadership, and work motivation on teacher performance with an effective contribution of 76.8%. These findings indicate that these three factors play an important role in improving teacher performance. Therefore, efforts to improve teacher performance should be focused on improving the quality of supervisory supervision, principal leadership, and teacher work motivation.

Osteoarthritis patients exhibit an autonomic dysfunction with indirect sympathetic dominance

BackgroundOsteoarthritis (OA) is a chronic degenerative joint disease causing limited mobility and pain, with no curative treatment available. Recent in vivo studies suggested autonomic alterations during OA progression in patients, yet clinical evidence is scarce. Therefore, autonomic tone was analyzed in OA patients via heart rate variability (HRV) measurements.MethodsTime-domain (SDRR, RMSSD, pRR50) and frequency-domain (LF, HF, LF/HF) HRV indices were determined to quantify sympathetic and parasympathetic activities. In addition, perceived stress, WOMAC pain as well as serum catecholamines, cortisol and dehydroepiandrosterone-sulphate (DHEA-S) were analyzed. The impact of the grade of disease (GoD) was evaluated by linear regression analysis and correlations with clinical data were performed.ResultsGoD significantly impacted the autonomic tone in OA patients. All time-domain parameters reflected slightly decreased HRV in early OA patients and significantly reduced HRV in late OA patients. Moreover, frequency-domain analysis revealed decreased HF and LF power in all OA patients, reflecting diminished parasympathetic and sympathetic activities. However, LF/HF ratio was significantly higher in early OA patients compared to late OA patients and implied a clear sympathetic dominance. Furthermore, OA patients perceived significantly higher chronic stress and WOMAC pain levels compared to healthy controls. Serum cortisol and cortisol/DHEA-S ratio significantly increased with GoD and positively correlated with WOMAC pain. In contrast, serum catecholamines only trended to increase with GoD and pain level.ConclusionsThis prospective study provides compelling evidence of an autonomic dysfunction with indirect sympathetic dominance in early and late knee OA patients for the first time based on HRV analyses and further confirmed by serum stress hormone measurements. Increased sympathetic activity and chronic low-grade inflammation in OA as well as in its major comorbidities reinforce each other and might therefore create a vicious cycle. The observed autonomic alterations coupled with increased stress and pain levels highlight the potential of HRV as a prognostic marker. In addition, modulation of autonomic activity represents an attractive future therapeutic option.Graphical abstract

Financial Crises and Economic Downturns of Commercial Banks in North Rift Region, Kenya

Financial Crises and Economic Downturns of Commercial Banks in North Rift Region, Kenya

PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection

The challenge of developing an Android malware detection framework that can identify malware in real-world apps is difficult for academicians and researchers. The vulnerability lies in the permission model of Android. Therefore, it has attracted the attention of various researchers to develop an Android malware detection model using permission or a set of permissions. Academicians and researchers have used all extracted features in previous studies, resulting in overburdening while creating malware detection models. But, the effectiveness of the machine learning model depends on the relevant features, which help in reducing the value of misclassification errors and have excellent discriminative power. A feature selection framework is proposed in this research paper that helps in selecting the relevant features. In the first stage of the proposed framework, t-test, and univariate logistic regression are implemented on our collected feature data set to classify their capacity for detecting malware. Multivariate linear regression stepwise forward selection and correlation analysis are implemented in the second stage to evaluate the correctness of the features selected in the first stage. Furthermore, the resulting features are used as input in the development of malware detection models using three ensemble methods and a neural network with six different machine-learning algorithms. The developed models’ performance is compared using two performance parameters: F-measure and Accuracy. The experiment is performed by using half a million different Android apps. The empirical findings reveal that malware detection model developed using features selected by implementing proposed feature selection framework achieved higher detection rate as compared to the model developed using all extracted features data set. Further, when compared to previously developed frameworks or methodologies, the experimental results indicates that model developed in this study achieved an accuracy of 98.8%.

Topological indices & Hirshfeld pseudo-surfaces synergy to understand the radiation attenuation in materials: Case of study spinel mineral crystals

The present work deals with the radiation attenuation characteristics of spinel minerals, a unique class of minerals with diverse crystalline structures and chemical compositions. We analyze the MAC and LAC in various photon energy spectrum using XCOM and Phys-X software tools. In addition to traditional methods, we employ topological indices (TIs) and Hirshfeld pseudo-surfaces (HPSs) to explore the atomic interactions and electron density distributions within these minerals to pinpointed their effects on the on these γ-radiation attenuation coefficients. Our findings reveal that MAC values decrease with increasing photon energy, a trend observed across all studied spinel minerals. The use of the HPSs provides visual insights into electron density distributions and intermolecular interactions mastered by 2D fingerprints which are correlated with the γ-attenuation of these spinels crystal. Linear regression correlations between TIs and MAC, LAC values demonstrate strong relationships, with the first Zagreb coindex and the Forgotten Index (F-index) emerging as reliable predictors of γ-rays radiations shield properties.

Detection Determinants of Bank Sustainability Report

Abstract Purpose - This study aims to determine the effect of board gender diversity, narcissism, and audit committee meeting intensity on sustainability reports in the banking company sub-sector listed on the Indonesia Stock Exchange (IDX) for 2018-2022. Design/methodology/approach - This study is a quantitative study that uses secondary data, namely data that has been processed in finished form and has been published. The population in this study are banking company sub-sector listed on the Indonesia Stock Exchange (IDX) for 2018-2022. The sample in this study was 12 companies with five years of observation using purposive sampling techniques to obtain 60 samples. The data analysis techniques used in this study are classical assumption test analysis, multiple linear regression test, correlation test, determination test, and t-test using SPSS 27 software. Findings - The results showed board gender diversity has a negative effect on sustainability reports, narcissism does not affect sustainability report, and audit committee meeting intensity has a positive effect on sustainability reports.Research limitations/implications - This research also provides a basis for further research into the relationship between organizational factors, leadership, and sustainability. Keywords: Board Gender Diversity, Narcissism, Audit Committee, and Sustainability Report Disclosure

Evaluation of The Relationship Between Dental and Cervical Vertebrae Maturation in Terms of Age Determination

Aim: Age determination is a very important issue in anthropology, forensic science, and dentistry. Today, the most commonly used methods for age determination are the methods in which tooth and bone development are evaluated. This study aims to evaluate the relationship between gender, chronological age, dental maturation, and cervical vertebral maturation in individuals aged 8-25 years. Material and Method: Digital panoramic, lateral cephalometric radiographs of 500 patients aged 8-25 years were used in this study. Cervical vertebra maturation was evaluated using the dental maturation-modified Demirjian classification system of Baccetti et al. Means, minimum, maximum, and standard deviations were calculated and analyzed as descriptive statistics. Kolmogorov-Smirnov, Kappa, Kruskal-Wallis, Chi-Square, Linear Regression, and Spearman Correlation tests were used for statistical analysis. Results: There was a statistically significant difference between chronological age and dental maturation and cervical vertebral maturation levels (p &lt;0.01). While dental maturation levels did not differ significantly according to gender (p&gt; 0.05), cervical vertebra maturation was statistically different (p &lt;0.01). There was a positive correlation between chronological age and dental maturation, and cervical vertebral maturation levels (p &lt;0.01). There was a strong correlation between dental maturation and cervical vertebral maturation levels (p &lt;0.01). Conclusion: The findings of this study showed that skeletal maturity increased with the increase in chronological and dental age for both genders. The earlier formation was consistently observed for each stage of skeletal maturation in females. All correlations between skeletal and dental maturations were statistically significant.

Analisis Keterampilan Penggunaan Alat Ukur terhadap Pemahaman Konsep pada Materi Besaran dan Satuan

This research aims to analyze the correlation between skills in using measuring instruments and understanding the concept of quantities and units in semester 1 students of the Physics Education study program at Madura Islamic University. The research method used is a quantitative approach with a pre-experimental approach. The sample in this research involved semester 1 students of the Madura Islamic University physics education study program who were taking basic physics 1 courses. Data collected in this research was through the distribution of essays regarding understanding the concept of quantities and units (Y) as well as skills in using measuring instruments (X ) with certain indicators. The values obtained from this research were analyzed using the SPSS statistical application with linear regression tests and correlation tests. The results of data analysis show that the correlation value = -0.384 with a significant value = 0.244 and Rsquare = 0.147. Based on the data analysis, it can be concluded that there is a negative correlation and does not have a significant impact on skills in using measuring instruments on understanding the concept of quantities and units. Skills in using measuring instruments contribute 14.7% to understanding the concept of quantities and units, while 85.3% is influenced by other factors.

Decoding cardiovascular risks: analyzing type 2 diabetes mellitus and ASCVD gene expression.

ASCVD is the primary cause of mortality in individuals with T2DM. A potential link between ASCVD and T2DM has been suggested, prompting further investigation. We utilized linear and multivariate logistic regression, Wilcoxon test, and Spearman's correlation toanalyzethe interrelation between ASCVD and T2DM in NHANES data from 2001-2018.The Gene Expression Omnibus (GEO) database and Weighted Gene Co-expression Network Analysis (WGCNA) wereconducted to identify co-expression networks between ASCVD and T2DM. Hub genes were identified using LASSO regression analysis and further validated in two additional cohorts. Bioinformatics methods were employed for gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, along with the prediction of candidate small molecules. Our analysis of the NHANES dataset indicated a significant impact of blood glucose on lipid levels within diabetic cohort, suggesting that abnormal lipid metabolism is a critical factor in ASCVD development. Cross-phenotyping analysis revealed two pivotal genes, ABCC5 and WDR7, associated with both T2DM and ASCVD. Enrichment analyses demonstrated the intertwining of lipid metabolism in both conditions, encompassing adipocytokine signaling pathway, fatty acid degradation and metabolism, and the regulation of adipocyte lipolysis. Immune infiltration analysis underscored the involvement of immune processes in both diseases. Notably, RITA, ON-01910, doxercalciferol, and topiramate emerged as potential therapeutic agents for both T2DM and ASCVD, indicating their possible clinical significance. Our findings pinpoint ABCC5 and WDR7 as new target genes between T2DM and ASCVD, with RITA, ON-01910, doxercalciferol, and topiramate highlighted as promising therapeutic agents.

Association of cardiovascular risk factors and myocardial hypertrophy in women with preeclampsia history

AimsA historic of preeclampsia (PE) has been associated with cardiovascular disease (CVD) in women. There are substantial evidences that cardiovascular changes resulting from PE can persist even after pregnancy end. Therefore, the aims was to evaluate the prevalence of myocardial hypertrophy in young women 12 months after PE event as well as try to identify risk factors for these changes. Materials and methodsSingle-center observational prospective cross-sectional study that included 118 consecutive patients after 12 months of PE. Clinical and laboratory evaluations, echocardiogram were performed. Myocardial hypertrophy (LVH) was defined as an index myocardial mass ≥ 45 g/m2.7, for women. Classical risk factors for CVD were considered. Analysis included linear or logistic regression and Spearman's correlation coefficient. Significance level of 5 %. Key findingsSystemic arterial hypertension (SAH) was identified in 52 patients (44 %), overweight/obesity (OOB) in 82 (69 %), dyslipidemia in 68 (57 %) and metabolic syndrome in 47 patients (40 %). LVH was present in 35 cases (29 %) and associated with OOB (OR = 4.51; CI95%:1.18–17.17, p < 0.001), in a model corrected for age and SAH diagnosis. When only the metabolic syndrome components were analyzed, in the multiple logistic regression model, the abdominal circumference was the only clinical variable associated with LVH (OR = 17.65; CI95%:3.70–84.17; p < 0.001). SignificanceIt was observed a high prevalence of ventricular hypertrophy in young women with a history of pre-eclampsia. This condition was associated with the presence of obesity.

Commitment to Sport Changes Psychological Needs: A Study on Individuals Who Regularly Engage in Fitness

It is as important to be able to continue sport as it is to start sport. In some sports branches, not practicing sports may cause some psychological problems. For this reason, this study aims to explain what changes individuals who train 3 days a week for at least 12 months in bodybuilding centers feel when they disrupt their training program and to show the relationship between their psychological needs in sports and their commitment to sports. The sample group of the study, in which quantitative and qualitative research model was used, consisted of 249 people (66 female, 183 male) who participated in sports for body development. Personal information form, open-ended questionnaire, sport psychological needs scale and sport commitment scale were used for the research. Content analysis was used in the qualitative data analysis of the study. Linear regression and Pearson correlation analysis were used for quantitative data analysis. The results of the qualitative data study show that the participants have positive emotions when they exercise and negative emotions when they do not exercise. The examination of quantitative data revealed that there was a positive weak relationship between psychological needs and sport addiction of the research group. In the study, it was concluded that the participant group enjoyed life, felt more talented, and were happy when they practiced sports, while when they did not spend time on sports, they felt a lack of time in their lives and experienced a sense of dissatisfaction. Keywords: Fitness, Commitment to sport, psychological needs in sport, chronic exercise

Analysis of Vegetation Environmental Stress and the Lag Effect in Countries along the “Six Economic Corridors”

Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

Investigating the properties of octane isomers by novel neighborhood product degree-based topological indices

A topological index is a real number calculated from the structure of a chemical compound to describe its topology. The use of molecular descriptors has been increasing in recent years, helping to determine the physicochemical and biological properties of drugs. The main purpose of this article is to investigate the properties of the octane isomers using the theoretical method. To study the structures of octane isomers, we have introduced a new approach called “neighborhood product degree” to calculate all the classical degree-based topological indices. The np-degree approach is applied to approximate eight properties of octane isomers, such as the acentric factor, density, refractive index, critical volume, molar volume, radius of curvature, critical pressure, and LogP. The np-degree-based topological indices are the estimated values of the properties of octane structures, so the linear and quadratic regression models and correlation coefficients are applied to check the validity of the estimated results. The quantitative structure property relation are obtained by using the linear, quadratic, exponential, logarithmic and sinusoidal regression methods with the help of SPSS. Two models are applied to all the compuations and three regression models are applied to the np-degree Randic index. The computation showed that quadratic regression model is suitable for study octane isomers and np-degree based graph invariants. If the values of the correlation coefficient r ⩾ 0.7, p-values ⩽ 0.05, and F-values ⩾ 2.5, then the results are significant. The results of np-degree-based topological indices satisfy all the criteria for being significant, so these newly introduced indices are valid to study octane isomers. The information determined in this article is beneficial for chemists and pharmacists.

Sports participation after craniosynostosis repair: the critical role of post-operative guidance in parental decision-making.

Despite previous research supporting patient safety in sports after craniosynostosis surgery, parental anxiety remains high. This study sought to evaluate the role of healthcare providers in guiding patients and families through the decision-making process. Parents of children with repaired craniosynostosis were asked to assess sports involvement and parental decision-making in children ages 6 and older. Questions were framed primarily on 5-point Likert scales. Sport categorizations were made in accordance with the American Academy of Pediatrics. Chi-squared, linear regression, and Pearson correlation tests were used to analyze associations between the questions. Forty-three complete parental responses were recorded. Mean ages at surgery and time of sports entry were 7.93 ± 4.73months and 4.76 ± 2.14years, respectively. Eighty-two percent of patients participated in a contact sport. Discussions with the primary surgeon were more impactful on parental decisions about sports participation than those with other healthcare providers (4.04 ± 1.20 vs. 2.69 ± 1.32). Furthermore, children whose parents consulted with the primary surgeon began participating in sports at a younger age (4.0 ± 1.0 vs. 5.8 ± 2.7years, p = 0.034). The mean comfort level with contact sports (2.8 ± 1.4) was lower than that with limited-contact (3.8 ± 1.1, p = 0.0001) or non-contact (4.4 ± 1.3, p < 0.0001) sports. This study underscores the critical role that healthcare professionals, primarily surgeons, have in guiding families through the decision-making process regarding their children's participation in contact sports.