Search Results (48)

Background: Effective mask ventilation is a very important aspect of ensuring adequate oxygenation and ventilation. However, predicting difficult mask ventilation (DMV) using bedside clinical tests remains challenging due to poor sensitivity. Our objective was to determine the correlation between the preoperative ultrasonography of anterior neck anatomy and difficult mask ventilation in different obesity classes. Methods: A prospective, observational study enrolled 90 adult obese patients undergoing general anesthesia from December 2020 to November 2021 (30 patients for each class of obesity). Ultrasonography measurements were recorded for the distance of skin (DS) to hyoid bone (DSHB), epiglottis (DSEM), the anterior commissure of the vocal cords (DSAC), thyroid isthmus (DSTI), and trachea at jugular notch (DSTJ). The difficulty of bag mask ventilation was graded using the Han scale. The Kendall Tau correlation coefficient was used to correlate the different ultrasonography parameters to DMV. Receiver-operating characteristic (ROC) curves were used to determine the sensitivity and specificity of the measured ultrasonography distances, and the Youden index was used to calculate the optimal cut-off values. Results: Results revealed twenty patients (22.2%) were categorized as having difficult mask ventilation. There was a statistically significant increase (p = 0.011) in the number of patients with Mallampati II in class III obesity compared to class I obesity. DSHB showed a statistically significant and strong correlation with difficult mask ventilation in patients with class II (p = 0.002, r = 0.464) and class III obesity (p = 0.002, r = 0.475). A DSHB cut-off value of 1.35 cm has a sensitivity of 83.3% and specificity of 78.8% for class III obesity. Similarly, a DSTJ cut-off value of 1.13 cm has a sensitivity of 83.3% and specificity of 66.7% for class III obesity. Conclusions: Notably, DSHB was the most specific parameter and equally as sensitive as DSTJ in predicting difficult mask ventilation in morbidly obese patients. Full article

The H-index is a widely recognized centrality measure for nodes in symmetric networks, defined as the maximum number of neighbors with degrees equal to or greater than the node’s own degree. However, this metric underestimates the structural influence of “weak nodes”—low-degree nodes connected to high-degree hubs—that often serve as critical connectors in network topology. To address this limitation, we propose the $H_{\alpha }$-index, which generalizes the H-index by considering the maximum number of neighbors with degrees at least $\alpha$ times the node’s degree, where $\alpha \ge 1$. Based on this refinement, we introduce two novel centrality measures: the g-core and the local g-core, which were derived from iterative applications of the $H_{\alpha }$-index to a node’s neighbors. Extensive experiments on sixteen real-world networks demonstrate the efficiency of our methods. Notably, the local g-core achieves 45–105% higher Kendall Tau correlation coefficients compared to the traditional H-index and coreness on three benchmark networks, highlighting its superior performance in capturing node influence. Full article

The lowering air pollution in the US has brought significant health benefits; however, climate change may offset the benefits by increasing the temperature and worsening air quality. This study aimed to estimate the mortality changes due to air pollution reductions and evaluate the potential climate penalty in the Mid-South Region of the US. Daily concentrations of PM_2.5 and ozone measured at local monitoring stations in 1999–2019 were extracted from the US Environmental Protection Agency’s Air Quality System. Meteorological data for the same period were obtained from the National Oceanic and Atmospheric Administration’s Local Climatological Data. Annual average age-adjusted all-cause mortality rates (MRs) were downloaded from the US Centers for Disease Control and Prevention’s WONDERS Databases. MRs attributable to exposure to PM_2.5, ozone, and high temperatures in warm months were estimated using their corresponding health impact functions. Using Year 1999 as the baseline, contributions of environmental changes to MR reductions were calculated. Results showed that annual average concentrations of PM_2.5 and ozone decreased by 46% and 23% in 2019, respectively, compared with the base year; meanwhile, the mean daily temperature in the warm season fluctuated and displayed an insignificant increasing trend (Kendall’s tau = 0.16, p = 0.30). MRs displayed a significant decreasing trend and dropped by 215 deaths/100,000 person-year in 2019. Lower PM_2.5 and ozone concentrations were estimated to reduce 59 and 30 deaths/100,000 person-year, respectively, contributing to 23% and 17% of MR reductions, respectively. The fluctuating temperatures had negligible impacts on mortality changes over the two-decade study period. This study suggests that improved air quality may have contributed to mortality reductions, while the climate penalty effects appeared to be insignificant in the Mid-South Region. Full article

This study introduces two bivariate extensions of the recently proposed weighted discretized Fréchet–Weibull distribution, termed as bivariate weighted discretized Fréchet–Weibull (BWDFW) distributions. These models are specifically designed for analyzing two-dimensional discrete datasets and are developed using two distinct structural approaches: the minimum operator (BWDFW-I) and the maximum operator (BWDFW-II). A rigorous mathematical formulation is presented, encompassing the joint cumulative distribution function, joint probability mass function, and joint (reversed) hazard rate function. The dependence structure of the models is investigated, demonstrating their capability to capture positive quadrant dependence. Additionally, key statistical measures, including covariance, Pearson’s correlation coefficient, Spearman’s rho, and Kendall’s tau, are derived using the joint probability-generating function. For robust statistical inferences, the parameters of the proposed models are estimated via the maximum likelihood estimation method, with extensive simulation studies conducted to assess the efficiency and accuracy of the estimators. The practical applicability of the BWDFW distributions is demonstrated through their implementation in two real-world datasets: one from the aviation sector and the other from the security and safety domain. Comparative analyses against four existing discrete bivariate Weibull extensions reveal the superior performance of the BWDFW models, with BWDFW-I (minimum operator based) exhibiting greater flexibility and predictive accuracy than BWDFW-II (maximum operator based). These findings underscore the potential of the BWDFW models as effective tools for modeling and analyzing bivariate discrete data in diverse applied contexts. Full article

Background/Objective: Early periodontitis diagnosis is challenging due to varying staging and grading systems. While clinical parameters like bleeding on probing (BoP) and pocket depth (PD) are commonly used, periapical radiographs provide valuable information about bone loss and periodontal ligament changes. However, a clear definition of early periodontitis, particularly regarding alveolar bone crest changes, remains elusive. Methods: This cross-sectional study involved 21 participants aged 20–30 with clinical signs of periodontitis and radiographic evidence of alveolar bone changes and periodontal ligament widening. Four dentists assessed 40 cases for BoP, 40 for PD, and 40 for periapical radiographs. Results: Statistical analysis revealed that the pocket depth measurement was the most significant factor in diagnosing early periodontitis (Fisher’s exact test, p-value = 0.000). Additionally, the irregularity of the alveolar crest proved to be a significant marker compared to periodontal ligament width (Fisher’s exact test, p-value = 0.000). A Kendall Tau_b test (p-value = 0.000, r = 1.000) confirmed pocket depth to be the most influential parameter among the assessed factors. Conclusions: While this study highlights the importance of clinical and radiographic assessments in early periodontitis detection, integrating these findings into a definitive diagnosis can be complex. The standardization of diagnostic techniques and the development of advanced radiographic interpretation methods are crucial to improve accuracy. Further research is needed to refine diagnostic criteria and explore additional tests for early periodontitis detection. Full article

Background: Person-centredness, a global movement in healthcare, is consistent with international developments in healthcare policy. It is important to have instruments to measure person-centred care. The Person-Centred Practice Inventory-Staff (PCPI-S) is an internationally recognized instrument that aims to measure how healthcare staff experience person-centred practice. Aim: To perform the cultural adaptation and psychometric testing of a Spanish version of the PCPI-S (PCPI-S (Sp)). Method: A two-stage research design was implemented as follows: (1) the translation and cultural adaptation of the PCPI-S from English to Spanish using the “Translation and Cultural Adaptation of Patient Reported Outcomes Measures-Principles of Good Practice”; (2) a quantitative cross-sectional survey for the psychometric evaluation of the PCPI-S. Test–retest reliability was evaluated using the Kendall tau concordance coefficient, internal reliability was assessed through the ordinal theta (OT) coefficient, and confirmatory factor analysis was performed to examine the theoretical measurement model. Results: A Spanish version of the PCPI-S was obtained. There were no significant difficulties in the translation process or the consulting sessions. A sample of 287 healthcare professionals participated in the study at least once. All the items showed at least a fair level of test–retest reliability. The OT scores were adequate (>0.69). The model showed good to adequate levels of fit: CFI = 0.89, SRMR = 0.068; RMSEA = 0.060 with CI90% (0.056–0.063). Conclusions: The Spanish translation of the PCPI-S was psychometrically valid when tested with Spanish healthcare professionals. This instrument will help identify professionals’ perceptions of person-centred practice, track the evolution of this practice over time, and assess interventions aimed at improving person-centred practice. Full article

Background/Objectives: Empowerment in medicine and psychiatry involves patients gaining control over health-related decisions, improving treatment adherence, outcomes, and satisfaction. This concept is especially significant in psychiatric care due to the complex challenges of mental health conditions, including stigma and impairment of emotional and cognitive functioning. We aim to investigate the correlations between patient trust, decision-making involvement, symptom severity, and perceived empowerment among individuals with Major Depression. Methods: Patients with Major Depressive Disorder were recruited in the “Policlinico G. Rodolico” psychiatry outpatient clinic from November 2022 to June 2023. Inclusion criteria: ages 18–65, ability to consent, stable condition, psychiatric medication history, and recent consultation. Exclusion criteria: psychotic features, bipolar disorder, substance abuse, high suicide risk, and severe comorbidities. Measures included the User Scale for Measuring Empowerment in Mental Health Services (SESM), Trust in Oncologist Scale (TiOS), Clinical Decision-Making Style for Patients (CDMS-P), and Hamilton Depression Rating Scale (HAM-D). Analysis used Kendall’s Tau correlation and Two-One-Sided Tests procedure. Results: Seventy-three patients completed the study. No relationship was found between decision-making involvement and perceived empowerment (τ = −0.0625; p = 0.448), or between trust in psychiatrists and empowerment (τ = 0.0747; p = 0.364). An inverse correlation existed between patient involvement in therapy management and trust (τ = −0.2505; p = 0.002). Depression severity inversely correlated with empowerment (τ = −0.2762; p = <.001), but not with trust or decision-making involvement. Conclusions: The lack of significant correlations suggests that decision-making involvement and trust alone may not suffice to enhance empowerment. Trust may encourage patient passivity, while skepticism might drive active involvement. Higher empowerment is associated with less depressive symptoms, highlighting its potential connection with patient outcomes. Full article

Aggression in farm animals affects welfare. Although one-on-one aggression was studied, group-on-individual aggression remains unresolved. This study aimed to examine how herd establishment times and structures influence aggression intensity (AI) of herds towards unfamiliar pigs. Six groups of pigs were established, with a new pig added every three days. AI was measured by skin lesion severity on the new pigs. A parabolic model based on the Levenberg–Marquardt algorithm and conjoint analysis identified factors influencing AI. Results show AI was not significantly affected by herd size but was significantly influenced by the number of pens (p < 0.01). AI showed a significant association with elevated time (T) since the establishment of the herd in six pig herds (Kendall’s tau-τ = 0.976, p < 0.001). The effect of T on the AI became stronger as T increased, which was consistently validated in six pig herds. Furthermore, the interaction effect indicates a significant difference in AI between herds formed with two pens and those with more than two pens when T ≤ 12 (p < 0.05). However, as T increased beyond 12, the number of pens used to form the herd did not significantly affect AI. These findings highlight the complex interactions between herd establishment time and structural composition in shaping aggression intensity towards unfamiliar pigs. Full article

Landslides cause significant economic losses and casualties worldwide. However, robust prediction remains challenging due to the complexity of geological factors contributing to slope stability. Advanced correlation analysis methods can improve prediction capabilities. This study aimed to develop a novel landslide prediction approach that combines numerical modeling and correlation analysis (Spearman rho and Kendall tau) to improve displacement-based failure prediction. Simulations generate multi-location displacement data sets on soil and rock slopes under incremental stability reductions. Targeted monitoring points profile local displacement responses. Statistical analyses, including mean/variance and Spearman/Kendall correlations, quantified displacement-stability relationships. For the homogeneous soil slope, monitoring point 2 of the middle section of the slope showed a mean horizontal displacement of 17.65 mm and a mean vertical displacement of 9.72 mm under stability reduction. Spearman’s rho correlation coefficients ranged from 0.31 to 0.76, while Kendall’s tau values ranged from 0.29 to 0.64, indicating variable displacement–stability relationships. The joint rock slope model had strong positive total displacement correlations (Spearman’s and Kendall’s correlation ranges of +1.0 and −1.0) at most points. Horizontal and vertical displacements reached mean maxima of 44.13 mm and 22.17 mm, respectively, at the unstable point 2 of the center section of the slope. The advanced correlation analysis techniques provided superior identification of parameters affecting slope stability compared to standard methods. The generated predictive model dramatically improves landslide prediction capability, allowing preventive measures to be taken to mitigate future losses through this new approach. Full article

Conditional copulas are useful tools for modeling the dependence between multiple response variables that may vary with a given set of predictor variables. Conditional dependence measures such as conditional Kendall’s tau and Spearman’s rho that can be expressed as functionals of the conditional copula are often used to evaluate the strength of dependence conditioning on the covariates. In general, semiparametric estimation methods of conditional copulas rely on an assumed parametric copula family where the copula parameter is assumed to be a function of the covariates. The functional relationship can be estimated nonparametrically using different techniques, but it is required to choose an appropriate copula model from various candidate families. In this paper, by employing the empirical checkerboard Bernstein copula (ECBC) estimator, we propose a fully nonparametric approach for estimating conditional copulas, which does not require any selection of parametric copula models. Closed-form estimates of the conditional dependence measures are derived directly from the proposed ECBC-based conditional copula estimator. We provide the large-sample consistency of the proposed estimator as well as the estimates of conditional dependence measures. The finite-sample performance of the proposed estimator and comparison with semiparametric methods are investigated through simulation studies. An application to real case studies is also provided. Full article

This study aimed to evaluate the awareness, comprehension, and practices concerning forensic odontology among dental students and faculty at a Dental School in Cyprus. An online, cross-sectional, descriptive survey, employing an adapted, self-administered questionnaire, was disseminated to all dental students and faculty at the School of Dentistry, European University Cyprus, in November 2022. The survey assessed participants’ demographic information and explored their awareness with questions alluding to knowledge, attitudes and practices in forensic dentistry. Of those surveyed, 47 faculty members and 304 students responded, yielding response rates of 66.2% and 80%, respectively. Statistical analysis, including Kendall’s tau test and χ² test were employed to examine correlations and associations, with Cramer’s V used to measure the strength of significant associations. The predetermined significance level was α = 0.05. Awareness levels were assessed through participants’ responses to specific questions in the survey. It was revealed that 87% of faculty and 65% of students were familiar with forensic odontology. A noteworthy 94% of faculty and 85% of students recognized teeth as DNA repositories. A high percentage, 98% of faculty and 89% of students, acknowledged the role of forensic odontology in the identification of criminals and deceased individuals. Awareness of age estimation through dental eruption patterns was evident in 85% of faculty and 81.6% of students. A substantial proportion (80% of faculty) maintained dental records, while 78% of students recognized the importance of dental record-keeping in ensuring quality care. Interestingly, 57% of students and 64% of faculty were aware of the possibility of dentists testifying as expert witnesses. The majority, 95.7% of faculty and 85% of students, concurred that physical harm, scars, and behavioral alterations predominantly indicate child abuse. The findings, revealing robust awareness among respondents, underscore the importance of enhancing faculty engagement in relevant seminars to further strengthen their knowledge. Additionally, emphasizing improved record-keeping practices for potential forensic applications emerges as a crucial aspect. These insights have implications for refining dental education in Cyprus and enhancing forensic practices by promoting ongoing professional development and emphasizing meticulous record-keeping within the dental community. Full article

Climate change is a significant environmental challenge that affects water resources, agriculture, health, and other aspects of human life. Bivariate modeling is a statistical method used to analyze the relationship between variables such as rainfall and temperature. The Pearson correlation coefficient, Kendall’s tau, or Spearman’s rank correlation are some measures used for bivariate modeling. However, copula functions can describe the dependence structure between two or more variables and can be effectively used to describe the relationship between rainfall and temperature. Despite the literature on bivariate modeling of rainfalls and temperature being extensive, finding flexible and sophisticated bivariate models is sometimes difficult. In this paper, we use rotated copula functions that can arrange any type of dependence that is empirically detected, especially negative dependence. The methodology is applied to an Italian municipality’s bivariate daily time series of rainfall and temperature. The estimated rotated copula is significant and, therefore, can be used for simulating the effects of extreme events. Full article

Patients with sickle cell disease (SCD) require repeated blood sampling for hemoglobin (Hb) concentration measurements. The primary aim of this study was to compare non-invasive spectrophotometric hemoglobin (SpHb, g/dL) measurements to those taken via an automated hematology analyzer (Hb, g/dL) in patients with SCD visiting outpatient clinics and to investigate the correlations and agreements between both measurement techniques. Secondarily, we aimed to identify the SpHb cut-off concentration for the diagnosis of anemia and to monitor the effects of the pleth variability index (PVI, %) and perfusion index (PI) on SpHb measurements. The results gained from the examination of one hundred and fifty-eight patients indicated that the SpHb measurements overestimated the lab Hb concentrations, with a mean (SpHb-Hb) bias of 0.82 g/dL (SD 1.29). The SpHb measurements were positively correlated with the Hb measurements (Kendall’s tau correlation (τ), n = 158, τ = 0.68, p < 0.001), with an intra-class correlation (ICC) of 0.67 and a 95% CI from 0.57 to 0.74 (p = 0.000). The SpHb cut-off concentration to diagnose anemia was 11.4 and 11.7 g/dL for males and females, respectively. SpHb sensitivity was low for males and females at 64.4% and 57.1%; however, the specificity was higher at 90.9% and 75%, with positive predictive values (PPVs) of 95.6 and 85.7, respectively. No correlation existed between SpHb measurements and the PVI (%) in contrast with a moderate correlation with the PI (r = 0.049, p = 0.54, and r = 0.36, p < 0.001, respectively). The mean PI was low at 2.52 ± 1.7. In conclusion, the SpHb measurements were consistently higher than the lab Hb concentrations, with a positive correlation. The sensitivity and precision of the SpHb measurements were lower than expected. However, the SpHb specificity and its positive predictive values (PPVs) indicated that it is less likely for a patient with a positive SpHb test result for anemia to be non-anemic. These results will allow SpHb measurement to play a role in excluding the presence of anemia. In light of the low PI values determined, the SpHb measurements were challenging to take and, thus, require further technological improvements. Full article

An accurate rating of hand activity and force is essential in risk assessment and for the effective prevention of work-related musculoskeletal disorders. However, it is unclear whether the subjective ratings of workers and observers correlate to corresponding objective technical measures of exposure. Fifty-nine workers were video recorded while performing a hand-intensive work task at their workplace. Self-ratings of hand activity level (HAL) and force (Borg CR10) using the Hand Activity Threshold Limit Value^® were assessed. Four ergonomist observers, in two pairs, also rated the hand activity and force level for each worker from video recordings. Wrist angular velocity was measured using inertial movement units. Muscle activity in the forearm muscles flexor carpi radialis (FCR) and extensor carpi radialis (ECR) was measured with electromyography root mean square values (RMS) and normalized to maximal voluntary electrical activation (MVE). Kendall’s tau-b correlations were statistically significant between self-rated hand activity and wrist angular velocity at the 10th, 50th, and 90th percentiles (0.26, 0.31, and 0.23) and for the ratings of observers (0.32, 0.41, and 0.34). Significant correlations for force measures were found only for observer-ratings in five of eight measures (FCR 50th percentile 0.29, time > 10%MVE 0.43, time > 30%MVE 0.44, time < 5% −0.47) and ECR (time > 30%MVE 0.26). The higher magnitude of correlation for observer-ratings suggests that they may be preferred to the self-ratings of workers. When possible, objective technical measures of wrist angular velocity and muscle activity should be preferred to subjective ratings when assessing risks of work-related musculoskeletal disorders. Full article

This study investigated the attitude of young people (individuals aged 14–25 years old) towards environmental protection using the NEP scale. The research aims to understand how demographic characteristics may influence young people’s attitudes toward green issues. The study focuses on answering the following two research questions: Q1. How can the environmental attitudes of young individuals be systematically characterized and summarized? Q2. To what extent do demographic factors influence the environmental attitudes of young individuals? A computer-assisted data collection (CAPI) method was carried out in four European Capital of Culture cities from different countries (Estonia, Hungary, Lithuania, Romania) from April to June 2022. On the basis of this primary questionnaire survey, descriptive statistics and relationship analyses (Cramer’s V and Kendall’s tau) were used to analyze the collected data (n = 712). The results revealed that in most cases, demographic characteristics had little or no impact at all on green attitudes. Thus, most youth attitudes showed the concept that humanity must adapt to the limits of nature. Furthermore, there were three green attitude statements where moderate differences could be detected by the countries. The findings can provide guidance for decision-makers in the field of environmental education and marketing, and they can also serve as a benchmark for other countries. Additionally, it opens up new opportunities for further research on the role of formal and informal education, as well as to measure the impact of social media on youth environmental behavior and their proactivity towards green issues. Full article