Moments of generalized order statistics appear in several areas of science and engineering.These moments are useful in studying properties of the random variables which are arranged in increasing order of importance,f...Moments of generalized order statistics appear in several areas of science and engineering.These moments are useful in studying properties of the random variables which are arranged in increasing order of importance,for example,time to failure of a computer system.The computation of these moments is sometimes very tedious and hence some algorithms are required.One algorithm is to use a recursive method of computation of these moments and is very useful as it provides the basis to compute higher moments of generalized order statistics from the corresponding lower-order moments.Generalized order statistics pro-vides several models of ordered data as a special case.The moments of general-ized order statistics also provide moments of order statistics and record values as a special case.In this research,the recurrence relations for single,product,inverse and ratio moments of generalized order statistics will be obtained for Lindley–Weibull distribution.These relations will be helpful for obtained moments of gen-eralized order statistics from Lindley–Weibull distribution recursively.Special cases of the recurrence relations will also be obtained.Some characterizations of the distribution will also be obtained by using moments of generalized order statistics.These relations for moments and characterizations can be used in differ-ent areas of computer sciences where data is arranged in increasing order.展开更多
In this paper explicit expressions and some recurrence relations are derived for marginal and joint moment generating functions of generalized order statistics from Erlang-truncated exponential distribution. The resul...In this paper explicit expressions and some recurrence relations are derived for marginal and joint moment generating functions of generalized order statistics from Erlang-truncated exponential distribution. The results for k-th record values and order statistics are deduced from the relations derived. Further, a characterizing result of this distribution on using the conditional expectation of function of generalized order statistics is discussed.展开更多
For characterization of negative exponential distribution one needs any arbitrary non constant function only in place of approaches such as identical distributions, absolute continuity, constancy of regression of orde...For characterization of negative exponential distribution one needs any arbitrary non constant function only in place of approaches such as identical distributions, absolute continuity, constancy of regression of order statistics, continuity and linear regression of order statistics, non-degeneracy etc. available in the literature. Recently Bhatt characterized negative exponential distribution through expectation of non constant function of random variable. Attempt is made to extend the characterization of negative exponential distribution through expectation of any arbitrary non constant function of order statistics.展开更多
For characterization of Pareto distribution one needs any arbitrary non constant function only by approach of identity of distribution and equality of expectation of function of random variable in place of approaches ...For characterization of Pareto distribution one needs any arbitrary non constant function only by approach of identity of distribution and equality of expectation of function of random variable in place of approaches such as relation （linear） in （economic variation） reported and true income, independency of suitable function of order statistics, mean and the extreme observation of the sample etc. Examples are given for illustrative purpose展开更多
Mixtures of lifetime distributions occur when two different causes of failure arc present, each with the same parametric form of lifetime distributions. This paper is considered with the mixture model of exponentiated...Mixtures of lifetime distributions occur when two different causes of failure arc present, each with the same parametric form of lifetime distributions. This paper is considered with the mixture model of exponentiated Rayleigh and exponentiated exponential distributions. The author＇s objectives are finding the statistical properties of the model and estimating the parameters of the model by using point estimation and interval estimation methods. First, some properties of the model with some graphs of the density function are discussed. Next, the maximum likelihood method of estimation is used for estimating scale and shape parameters of the model. Estimating the parameters is studied under complete and type II censored samples for different sample sizes. Asymptotic Fisher information matrix of the estimators for complete samples is founded with different sample sizes. The asymptotic variances of the maximum likelihood estimates are derived. Based on the asymptotic variances of the maximum likelihood estimates, interval estimates of the parameters are obtained. Some of the equations in this paper are solved by using numerical iteration such as Newton Raphson method by using Mathematica 7.0. The performance of findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation study based on absolute relative bias and mean square error.展开更多
Financial pressure of multifactorial etiology promises to create new obstacles for academic anesthesia departments. Integrating the priorities of the academic and clinical mission of the anesthesia department, the med...Financial pressure of multifactorial etiology promises to create new obstacles for academic anesthesia departments. Integrating the priorities of the academic and clinical mission of the anesthesia department, the medical school, and the university hospital will require that anesthesia departments operate with maximal operational efficiency. Maintenance or expansion of institutional infrastructural support of the university anesthesia department will be necessary to achieve operational efficiencies, and to ensure that the safety of our patients is in no way compromised by financial concerns. Previous studies have documented increasing need for monetary institutional supports of academic anesthesia departments [1]. The purpose of this study is to delineate non-monetary institutional support afforded to academic anesthesia departments by their University Hospitals. After IRB approval, we electronically solicited the response to a 63 question survey (43 of which were used for the present study) from all 133 chairpersons of academic anesthesia departments in the United States. The remaining 20 questions were unrelated to the topics presented in this manuscript. 62 responded electronically, for an overall response rate of 46.6%. This study establishes the current state of infrastructural support afforded to academic anesthesia departments in the United States.展开更多
BACKGROUND Although the link between cardiovascular disease(CVD)and various cancers is well-established,the relationship between CVD risk and colorectal cancer(CRC)remains underexplored.AIM To elucidate the relationsh...BACKGROUND Although the link between cardiovascular disease(CVD)and various cancers is well-established,the relationship between CVD risk and colorectal cancer(CRC)remains underexplored.AIM To elucidate the relationship between CVD risk scores and CRC incidence.METHODS In this population-based cohort study,participants from the 2009 National Health Checkup were followed-up until 2020.The cardiovascular(CV)risk score was calculated as the sum of risk factors(age,family history of coronary artery disease,hypertension,smoking status,and high-density lipoprotein levels)with high-density lipoprotein(≥60 mg/dL)reducing the risk score by one.The primary outcome was incidence of newly diagnosed CRC.RESULTS Among 2526628 individuals,30329 developed CRC during a mean follow-up of 10.1 years.Categorized by CV risk scores(0,1,2,and≥3).CRC risk increased with higher CV risk scores after adjusting for covariates[(hazard ratio=1.155,95%confidence interval:1.107-1.205)in risk score≥3,P<0.001].This association individuals not using statins.Moreover,even in participants without diabetes,a higher CV risk was associated with an increased CRC risk.CONCLUSION Increased CV risk scores were significantly associated with higher CRC risk,especially among males,younger populations,and non-statin users.Thus,males with a higher CV risk score,even at a younger age,are recommended to control their risk factors and undergo individualized CRC screening.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
Background: Suicidal attempt in children is a serious public health problem. A proper identification of features of suicide-related behavior may help physicians to develop an accurate approach. The aim of this study w...Background: Suicidal attempt in children is a serious public health problem. A proper identification of features of suicide-related behavior may help physicians to develop an accurate approach. The aim of this study was to clarify the characteristics of children with poisoning due to suicidal attempt and to determine the risk factors of suicidal re-attempt in the Emergency Department (ED) via a simple questionnaire. Methods: We collected medical data of patients under 18 years who were admitted to our ED with intoxication due to suicidal attempt, retrospectively. General characteristics of patients were evaluated. Patients were divided into 2 groups as 1) High risk: patients with repetitive suicide attempt;2) Low risk: patients with first time suicidal attempt. Results: A total of 57 patients were included in this study. The mean age was 15.91 ± 0.97. Majority of the patients were female (73.7%). Analgesics were the most frequent abused drugs with a ratio of 51.1%. It is determined that the most important variables affecting the risk of suicidal re-attempt are “idea about the suicide” and “purpose”. It was determined that patients with an idea of repetitive suicide (I will try again) and whose purpose was to die (I wish I have died) were in the most risky group with a history of previous suicidal attempt. Conclusion: This study suggests that answers of the pediatric patients to some question have a potential to predict the high risk patients. The risk of suicidal re-attempt may be predicted by the answers given to these questions: 1) What is your idea about suicide? 2) What was your purpose?展开更多
A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment ...A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment effect and interim result.For hypotheses and reversed hypotheses under normal models,we obtain analytical expressions of the ROC curves of the CCP,find optimal ROC curves of the CCP,investigate the superiority of the ROC curves of the CCP,calculate critical values of the False Positive Rate(FPR),True Positive Rate(TPR),and cutoff of the optimal CCP,and give go/no go decisions at the interim of the optimal CCP.In addition,extensive numerical experiments are carried out to exemplify our theoretical results.Finally,a real data example is performed to illustrate the go/no go decisions of the optimal CCP.展开更多
We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scen...We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scenario,in which the lifetime associated with a particular risk is not observable;rather,we observe only the maximum lifetime value among all risks.The distribution exhibits decreasing,increasing,unimodal and bathtub shaped hazard rate functions,depending on its parameters.Several properties of the EPLPS distribution are investigated.Moreover,we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix.Finally,applications to three real data sets show the flexibility and potentiality of the EPLPS distribution.展开更多
Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors f...Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors face an ever increasing scarcity of experts willing to act as reviewers.It is not infrequent that reviews diverge,which forces editors to recur to additional reviewers or make a final decision on their own.The purpose of the proposed bibliometric system is to support of editors’accept/reject decisions in such situations.Design/methodology/approach:We analyse nearly two million 2017 publications and their scholarly impact,measured by normalized citations.Based on theory and previous literature,we extrapolated the publication traits of text,byline,and bibliographic references expected to be associated with future citations.We then fitted a regression model with the outcome variable as the scholarly impact of the publication and the independent variables as the above non-scientific traits,controlling for fixed effects at the journal level.Findings:Non-scientific factors explained more than 26%of the paper’s impact,with slight variation across disciplines.On average,OA articles have a 7%greater impact than non-OA articles.A 1%increase in the number of references was associated with an average increase of 0.27%in impact.Higher-impact articles in the reference list,the number of authors and of countries in the byline,the article length,and the average impact of co-authors’past publications all show a positive association with the article’s impact.Female authors,authors from English-speaking countries,and the average age of the article’s references show instead a negative association.Research limitations:The selected non-scientific factors are the only observable and measurable ones to us,but we cannot rule out the presence of significant omitted variables.Using citations as a measure of impact has well-known limitations and overlooks other forms of scholarly influence.Additionally,the large dataset constrained us to one year’s global publications,preventing us from capturing and accounting for time effects.Practical implications:This study provides journal editors with a quantitative model that complements peer reviews,particularly when reviewer evaluations diverge.By incorporating non-scientific factors that significantly predict a paper’s future impact,editors can make more informed decisions,reduce reliance on additional reviewers,and improve the efficiency and fairness of the manuscript selection process.Originality/value:To the best of our knowledge,this study is the first one to specifically address the problem of supporting editors in any field in their decisions on submitted manuscripts with a quantitative model.Previous works have generally investigated the relationship between a few of the above publication traits and their impact or the agreement between peer-review and bibliometric evaluations of publications.展开更多
Objective This study aimed to develop a prediction model to assess the risk of sepsis-induced coagulopathy(SIC)in sepsis patients.Methods We conducted a retrospective study of septic patients admitted to the Intensive...Objective This study aimed to develop a prediction model to assess the risk of sepsis-induced coagulopathy(SIC)in sepsis patients.Methods We conducted a retrospective study of septic patients admitted to the Intensive Care Units of Shandong Provincial Hospital(Central Campus and East Campus),and Shenxian People’s Hospital from January 2019 to September 2024.We used Kaplan-Meier analysis to assess survival outcomes.LASSO regression identified predictive variables,and logistic regression was employed to analyze risk factors for pre-SIC.A nomogram prediction model was developed via R software and evaluated via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).Results Among 309 patients,236 were in the training set,and 73 were in the test set.The pre-SIC group had higher mortality(44.8%vs.21.3%)and disseminated intravascular coagulation(DIC)incidence(56.3%vs.29.1%)than the non-SIC group.LASSO regression identified lactate,coagulation index,creatinine,and SIC scores as predictors of pre-SIC.The nomogram model demonstrated good calibration,with an AUC of 0.766 in the development cohort and 0.776 in the validation cohort.DCA confirmed the model’s clinical utility.Conclusion SIC is associated with increased mortality,with pre-SIC further increasing the risk of death.The nomogram-based prediction model provides a reliable tool for early SIC identification,potentially improving sepsis management and outcomes.展开更多
BACKGROUND Decreased renal function is a well-known risk factor for cardiovascular diseases(CVD)and death.However,the impact of diabetes duration and the glomerular filtration rate(GFR)on cardiovascular complications ...BACKGROUND Decreased renal function is a well-known risk factor for cardiovascular diseases(CVD)and death.However,the impact of diabetes duration and the glomerular filtration rate(GFR)on cardiovascular complications in patients with type 2 dia-betes has not been well studied.AIM To investigate the complex impact of longer diabetes duration and GFR on CVD and mortality.METHODS Subjects with diabetes age≥20 years,who underwent health check-ups from 2015 to 2016 were identified in the Korean National Health Insurance Service database.Based on diabetes duration,subjects were grouped into new-onset,<5 years,5–9 years,or≥10 years.The new-onset diabetes group[estimated GFR(eGFR):≥90 mL/min/1.73 m2]was the reference group.A Cox proportional hazards model adjusted for potential confounders was used to estimate the risk for myocardial infarction(MI),ischemic stroke(IS),and mortality.RESULTS During a 3.9-year follow-up of 2105228 patients,36003(1.7%)MIs,46496(2.2%)ISs,and 73549(3.5%)deaths were documented.Both longer diabetes duration and lower eGFR were independently associated with higher risks of MI,IS,and mortality,which were further amplified when these factors coexisted.Even patients with new-onset diabetes had elevated MI and IS risk at mildly reduced eGFR(60–90 mL/min/1.73 m^(2)).Mortality risk rose appreciably once eGFR declined below 60 mL/min/1.73 m^(2),particularly in those with longer diabetes duration.eGFR≥90 mL/min/1.73 m2 subgroups had higher death risk than eGFR 60–90 mL/min/1.73 m2 subgroups regardless of diabetic duration.CONCLUSION Increasing diabetes duration and decreasing eGFR are associated with increased risk of MI,IS,and mortality.For cardiovascular risk estimation,diabetes duration should be considered an important risk factor.展开更多
1|Introduction Climate change is one of the most significant and widespread global issues,contributing to emerging infectious diseases and threatening human physical and mental health[1,2].Bangladesh,one of the most d...1|Introduction Climate change is one of the most significant and widespread global issues,contributing to emerging infectious diseases and threatening human physical and mental health[1,2].Bangladesh,one of the most densely populated countries in South Asia,experiences unpredictable weather and a steady increase in temperature and precipitation.Between 1901 and 2019,Bangladesh saw an average temperature increase of 0.5℃ according to the change in mean monthly temperatures.Warming is more pronounced in winter months,such as January(from 0.6℃ to 1.9℃)and November(1.3℃ to 1.8℃),compared to smaller increase during the monsoon(Figure 1).This reflects uneven seasonal warming,driven by climate change,with winter and pre-winter months experiencing the most significant temperature rises.展开更多
Biomass models to estimate carbon stocks in arid environment are very limited. This study employed destructive sampling to develop a new biomass model for Vachellia tortilis, a widely known species in the Sultanate of...Biomass models to estimate carbon stocks in arid environment are very limited. This study employed destructive sampling to develop a new biomass model for Vachellia tortilis, a widely known species in the Sultanate of Oman. Twenty trees with a diameter at stump height (DSH) ranging from 18.5 cm to 150 cm were selected based on DSH and height variations for destructive sampling in As Saleel Natural Park Reserve (SNPR) in Al Sharqiyah governorate, South of Oman. Each tree was excavated and cut into three parts: Stems, Branches, twigs, and leaves. The total fresh weight of each tree was obtained in the field using a 300 balance. Sub-samples (250 - 300 grams) were taken from each part of the tree and transferred to the laboratory for dry weight determination. Linear multiple regression analysis was done using SPSS software between the three variables, DSH, H, CA (x) and the total dry biomass (y). Five models were tested for the best-fit model based on R-Square and Mean Square Error (MSE). Model 5 was the best-fit model, including the LOG of DSH and the LOG of CA (R2 = 0.97, MSE = 0.114). The models developed in this research fill a critical gap in estimating the AGB of terrestrial native species in Oman and other countries with similar ecological and climate conditions.展开更多
BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship ...BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship between exercise intensity,DM duration,and ESRD incidence.METHODS This retrospective cohort study analyzed data from 2495031 individuals with DM who underwent the Korean National Health Screening between 2015 and 2016,with follow-up through 2022.The Cox proportional hazards model was adjusted for confounders,including age,sex,income,smoking,and baseline comorbidities.RESULTS Longer DM duration was associated with a significantly higher risk of ESRD,with durations≥10 years showing the highest risk[hazard ratio(HR):2.624,95%confidence interval(CI):2.486-2.770].Increased exercise intensity reduced the risk of developing ESRD across all diabetes duration groups,with the highest exercise category(≥1500 metabolic equivalents of task-min/week)demonstrating a protective effect compared to that of no exercise(HR:0.837,95%CI:0.791-0.886).Exercise benefits were more pronounced in patients without hypertension,non-smokers,and those with lower alcohol consumption.Additionally,ESRD risk reduction was significant among patients with a body mass index≥25 and those without proteinuria or chronic kidney disease.CONCLUSION Longer diabetes duration is associated with increased ESRD risk,while high-intensity exercise may mitigate this risk.These findings suggest promoting exercise is important for managing diabetes to reduce renal complications.展开更多
Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart d...Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.展开更多
BACKGROUND Diabetes is a significant risk factor for chronic kidney disease,and diabetic kidney disease(DKD)is prevalent among patients with diabetes.Previous studies have indicated that the duration of diabetes and p...BACKGROUND Diabetes is a significant risk factor for chronic kidney disease,and diabetic kidney disease(DKD)is prevalent among patients with diabetes.Previous studies have indicated that the duration of diabetes and poor glycemic control are associated with an increased risk of DKD,but data on how the duration and severity of hyperglycemia specifically relate to DKD progression are limited.AIM To investigate the relationship between diabetes duration and glycemic control,and DKD progression in South Korea.METHODS We included 2303 patients with diabetes using the 2019-2021 Korea National Health and Nutrition Examination Surveys data.DKD was defined as an estimated glomerular filtration rate(eGFR)<60 mL/min per 1.73 m2,urinary albumin-to-creatinine ratio≥30 mg/g,or both.Diabetes duration and severity were classified into six categories each.RESULTS DKD prevalence was 25.5%.The DKD risk significantly increased in diabetes lasting 10-15 years or hemoglobin A1C(HbA1c)≥8%compared to patients with newly diagnosed diabetes or HbA1c<6.5%.Albuminuria developed with shorter diabetes duration and lower HbA1c than eGFR decline.The adjusted odds ratios for DKD were 3.77[95%confidence interval(95%CI):2.60-5.45]and 4.91(95%CI:2.80-8.63)in patients with diabetes lasting≥20 years and HbA1c≥10%,respectively,compared to those with new-onset diabetes and HgA1c<6.5%.CONCLUSION Patients with diabetes lasting>10 years or HbA1c>8%had a higher risk of DKD,emphasizing the importance of early monitoring and management is crucial to prevent DKD progression.展开更多
Objective:Cardiopulmonary resuscitation(CPR)is one of the most important life-saving procedures in the hospital.Contrary to medical guidelines,family presence during CPR is still not accepted in some countries.Family ...Objective:Cardiopulmonary resuscitation(CPR)is one of the most important life-saving procedures in the hospital.Contrary to medical guidelines,family presence during CPR is still not accepted in some countries.Family presence during CPR depends on the nurses’attitude,which is influenced by various factors.Emotional intelligence(EI)helps nurses make wise decisions and display responsible behavior,which is necessary for proper and good performance in nursing.The study’s purpose was to determine the attitude of acute care nurses toward family presence during CPR and its relationship with EI.Methods:The descriptive-analytical study was conducted among the nurses of acute care units(intensive care unit[ICU],critical care unit,and emergency department)in teaching hospitals of Qazvin University of Medical Sciences,Iran,in 2022-2023.A total of 186 nurses were included in the study using convenience sampling.The data collection tools were a checklist of demographic characteristics,nurses’attitude toward the presence of family scale,and Siberia Schering’s EI questionnaire.The collected data were analyzed using descriptive and analytical statistics and SPSS software.Results:The mean age of the participants was(32.05±6.93)years.Of 186 nurses participating in the study,127(68.3%)were women and the rest were men.The mean score of attitude was 47.41±9.41(the minimum score of the nurses was 19 and the maximum score was 95).The mean score of EI was 99.27±8.86(the minimum score was 69 and the maximum score was 128).The results of Pearson’s correlation coefficient showed no significant relationship between the total score of attitude and EI of the participants(P=0.588).Data analysis showed that only the self-arousal dimension of EI has a significant relationship with the range of family self-control behaviors in attitude(P=0.037).Conclusions:The results showed that the nurses of acute care units have a positive attitude toward the presence of the family during CPR and have high EI.Although no significant relationship was observed between the 2 variables,paying attention to the influencing factors on the attitude of the nurse toward family presence during CPR in different societies needs more research and investigation.展开更多
基金The work was funded by the University of Jeddah,Saudi Arabia under Grant Number UJ–02–093–DR.The authors,therefore,acknowledge with thanks the University for technical and financial support.
文摘Moments of generalized order statistics appear in several areas of science and engineering.These moments are useful in studying properties of the random variables which are arranged in increasing order of importance,for example,time to failure of a computer system.The computation of these moments is sometimes very tedious and hence some algorithms are required.One algorithm is to use a recursive method of computation of these moments and is very useful as it provides the basis to compute higher moments of generalized order statistics from the corresponding lower-order moments.Generalized order statistics pro-vides several models of ordered data as a special case.The moments of general-ized order statistics also provide moments of order statistics and record values as a special case.In this research,the recurrence relations for single,product,inverse and ratio moments of generalized order statistics will be obtained for Lindley–Weibull distribution.These relations will be helpful for obtained moments of gen-eralized order statistics from Lindley–Weibull distribution recursively.Special cases of the recurrence relations will also be obtained.Some characterizations of the distribution will also be obtained by using moments of generalized order statistics.These relations for moments and characterizations can be used in differ-ent areas of computer sciences where data is arranged in increasing order.
文摘In this paper explicit expressions and some recurrence relations are derived for marginal and joint moment generating functions of generalized order statistics from Erlang-truncated exponential distribution. The results for k-th record values and order statistics are deduced from the relations derived. Further, a characterizing result of this distribution on using the conditional expectation of function of generalized order statistics is discussed.
文摘For characterization of negative exponential distribution one needs any arbitrary non constant function only in place of approaches such as identical distributions, absolute continuity, constancy of regression of order statistics, continuity and linear regression of order statistics, non-degeneracy etc. available in the literature. Recently Bhatt characterized negative exponential distribution through expectation of non constant function of random variable. Attempt is made to extend the characterization of negative exponential distribution through expectation of any arbitrary non constant function of order statistics.
文摘For characterization of Pareto distribution one needs any arbitrary non constant function only by approach of identity of distribution and equality of expectation of function of random variable in place of approaches such as relation （linear） in （economic variation） reported and true income, independency of suitable function of order statistics, mean and the extreme observation of the sample etc. Examples are given for illustrative purpose
文摘Mixtures of lifetime distributions occur when two different causes of failure arc present, each with the same parametric form of lifetime distributions. This paper is considered with the mixture model of exponentiated Rayleigh and exponentiated exponential distributions. The author＇s objectives are finding the statistical properties of the model and estimating the parameters of the model by using point estimation and interval estimation methods. First, some properties of the model with some graphs of the density function are discussed. Next, the maximum likelihood method of estimation is used for estimating scale and shape parameters of the model. Estimating the parameters is studied under complete and type II censored samples for different sample sizes. Asymptotic Fisher information matrix of the estimators for complete samples is founded with different sample sizes. The asymptotic variances of the maximum likelihood estimates are derived. Based on the asymptotic variances of the maximum likelihood estimates, interval estimates of the parameters are obtained. Some of the equations in this paper are solved by using numerical iteration such as Newton Raphson method by using Mathematica 7.0. The performance of findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation study based on absolute relative bias and mean square error.
文摘Financial pressure of multifactorial etiology promises to create new obstacles for academic anesthesia departments. Integrating the priorities of the academic and clinical mission of the anesthesia department, the medical school, and the university hospital will require that anesthesia departments operate with maximal operational efficiency. Maintenance or expansion of institutional infrastructural support of the university anesthesia department will be necessary to achieve operational efficiencies, and to ensure that the safety of our patients is in no way compromised by financial concerns. Previous studies have documented increasing need for monetary institutional supports of academic anesthesia departments [1]. The purpose of this study is to delineate non-monetary institutional support afforded to academic anesthesia departments by their University Hospitals. After IRB approval, we electronically solicited the response to a 63 question survey (43 of which were used for the present study) from all 133 chairpersons of academic anesthesia departments in the United States. The remaining 20 questions were unrelated to the topics presented in this manuscript. 62 responded electronically, for an overall response rate of 46.6%. This study establishes the current state of infrastructural support afforded to academic anesthesia departments in the United States.
文摘BACKGROUND Although the link between cardiovascular disease(CVD)and various cancers is well-established,the relationship between CVD risk and colorectal cancer(CRC)remains underexplored.AIM To elucidate the relationship between CVD risk scores and CRC incidence.METHODS In this population-based cohort study,participants from the 2009 National Health Checkup were followed-up until 2020.The cardiovascular(CV)risk score was calculated as the sum of risk factors(age,family history of coronary artery disease,hypertension,smoking status,and high-density lipoprotein levels)with high-density lipoprotein(≥60 mg/dL)reducing the risk score by one.The primary outcome was incidence of newly diagnosed CRC.RESULTS Among 2526628 individuals,30329 developed CRC during a mean follow-up of 10.1 years.Categorized by CV risk scores(0,1,2,and≥3).CRC risk increased with higher CV risk scores after adjusting for covariates[(hazard ratio=1.155,95%confidence interval:1.107-1.205)in risk score≥3,P<0.001].This association individuals not using statins.Moreover,even in participants without diabetes,a higher CV risk was associated with an increased CRC risk.CONCLUSION Increased CV risk scores were significantly associated with higher CRC risk,especially among males,younger populations,and non-statin users.Thus,males with a higher CV risk score,even at a younger age,are recommended to control their risk factors and undergo individualized CRC screening.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
文摘Background: Suicidal attempt in children is a serious public health problem. A proper identification of features of suicide-related behavior may help physicians to develop an accurate approach. The aim of this study was to clarify the characteristics of children with poisoning due to suicidal attempt and to determine the risk factors of suicidal re-attempt in the Emergency Department (ED) via a simple questionnaire. Methods: We collected medical data of patients under 18 years who were admitted to our ED with intoxication due to suicidal attempt, retrospectively. General characteristics of patients were evaluated. Patients were divided into 2 groups as 1) High risk: patients with repetitive suicide attempt;2) Low risk: patients with first time suicidal attempt. Results: A total of 57 patients were included in this study. The mean age was 15.91 ± 0.97. Majority of the patients were female (73.7%). Analgesics were the most frequent abused drugs with a ratio of 51.1%. It is determined that the most important variables affecting the risk of suicidal re-attempt are “idea about the suicide” and “purpose”. It was determined that patients with an idea of repetitive suicide (I will try again) and whose purpose was to die (I wish I have died) were in the most risky group with a history of previous suicidal attempt. Conclusion: This study suggests that answers of the pediatric patients to some question have a potential to predict the high risk patients. The risk of suicidal re-attempt may be predicted by the answers given to these questions: 1) What is your idea about suicide? 2) What was your purpose?
基金supported by the National Social Science Fund of China(Grand No.21XTJ001).
文摘A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment effect and interim result.For hypotheses and reversed hypotheses under normal models,we obtain analytical expressions of the ROC curves of the CCP,find optimal ROC curves of the CCP,investigate the superiority of the ROC curves of the CCP,calculate critical values of the False Positive Rate(FPR),True Positive Rate(TPR),and cutoff of the optimal CCP,and give go/no go decisions at the interim of the optimal CCP.In addition,extensive numerical experiments are carried out to exemplify our theoretical results.Finally,a real data example is performed to illustrate the go/no go decisions of the optimal CCP.
文摘We introduce a new generalization of the exponentiated power Lindley distribution,called the exponentiated power Lindley power series(EPLPS)distribution.The new distribution arises on a latent complementary risks scenario,in which the lifetime associated with a particular risk is not observable;rather,we observe only the maximum lifetime value among all risks.The distribution exhibits decreasing,increasing,unimodal and bathtub shaped hazard rate functions,depending on its parameters.Several properties of the EPLPS distribution are investigated.Moreover,we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix.Finally,applications to three real data sets show the flexibility and potentiality of the EPLPS distribution.
文摘Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors face an ever increasing scarcity of experts willing to act as reviewers.It is not infrequent that reviews diverge,which forces editors to recur to additional reviewers or make a final decision on their own.The purpose of the proposed bibliometric system is to support of editors’accept/reject decisions in such situations.Design/methodology/approach:We analyse nearly two million 2017 publications and their scholarly impact,measured by normalized citations.Based on theory and previous literature,we extrapolated the publication traits of text,byline,and bibliographic references expected to be associated with future citations.We then fitted a regression model with the outcome variable as the scholarly impact of the publication and the independent variables as the above non-scientific traits,controlling for fixed effects at the journal level.Findings:Non-scientific factors explained more than 26%of the paper’s impact,with slight variation across disciplines.On average,OA articles have a 7%greater impact than non-OA articles.A 1%increase in the number of references was associated with an average increase of 0.27%in impact.Higher-impact articles in the reference list,the number of authors and of countries in the byline,the article length,and the average impact of co-authors’past publications all show a positive association with the article’s impact.Female authors,authors from English-speaking countries,and the average age of the article’s references show instead a negative association.Research limitations:The selected non-scientific factors are the only observable and measurable ones to us,but we cannot rule out the presence of significant omitted variables.Using citations as a measure of impact has well-known limitations and overlooks other forms of scholarly influence.Additionally,the large dataset constrained us to one year’s global publications,preventing us from capturing and accounting for time effects.Practical implications:This study provides journal editors with a quantitative model that complements peer reviews,particularly when reviewer evaluations diverge.By incorporating non-scientific factors that significantly predict a paper’s future impact,editors can make more informed decisions,reduce reliance on additional reviewers,and improve the efficiency and fairness of the manuscript selection process.Originality/value:To the best of our knowledge,this study is the first one to specifically address the problem of supporting editors in any field in their decisions on submitted manuscripts with a quantitative model.Previous works have generally investigated the relationship between a few of the above publication traits and their impact or the agreement between peer-review and bibliometric evaluations of publications.
基金funded by the Shandong Provincial Natural Science Foundation(No.ZR2024MH008)Postdoctoral Innovation Program of Shandong Province(No.SDCX-ZG-202400043)Beijing iGandan Foundation(No.iGandanF-1082022-RGG007).
文摘Objective This study aimed to develop a prediction model to assess the risk of sepsis-induced coagulopathy(SIC)in sepsis patients.Methods We conducted a retrospective study of septic patients admitted to the Intensive Care Units of Shandong Provincial Hospital(Central Campus and East Campus),and Shenxian People’s Hospital from January 2019 to September 2024.We used Kaplan-Meier analysis to assess survival outcomes.LASSO regression identified predictive variables,and logistic regression was employed to analyze risk factors for pre-SIC.A nomogram prediction model was developed via R software and evaluated via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).Results Among 309 patients,236 were in the training set,and 73 were in the test set.The pre-SIC group had higher mortality(44.8%vs.21.3%)and disseminated intravascular coagulation(DIC)incidence(56.3%vs.29.1%)than the non-SIC group.LASSO regression identified lactate,coagulation index,creatinine,and SIC scores as predictors of pre-SIC.The nomogram model demonstrated good calibration,with an AUC of 0.766 in the development cohort and 0.776 in the validation cohort.DCA confirmed the model’s clinical utility.Conclusion SIC is associated with increased mortality,with pre-SIC further increasing the risk of death.The nomogram-based prediction model provides a reliable tool for early SIC identification,potentially improving sepsis management and outcomes.
基金Supported by the National Research Foundation of Korea grant funded by the Korea government,No.RS-2023-00217317the Korea Health Technology R and D Project through the Korea Health Industry Development Institute funded by the Ministry of Health and Welfare,Republic of Korea,No.RS-2024-00439029.
文摘BACKGROUND Decreased renal function is a well-known risk factor for cardiovascular diseases(CVD)and death.However,the impact of diabetes duration and the glomerular filtration rate(GFR)on cardiovascular complications in patients with type 2 dia-betes has not been well studied.AIM To investigate the complex impact of longer diabetes duration and GFR on CVD and mortality.METHODS Subjects with diabetes age≥20 years,who underwent health check-ups from 2015 to 2016 were identified in the Korean National Health Insurance Service database.Based on diabetes duration,subjects were grouped into new-onset,<5 years,5–9 years,or≥10 years.The new-onset diabetes group[estimated GFR(eGFR):≥90 mL/min/1.73 m2]was the reference group.A Cox proportional hazards model adjusted for potential confounders was used to estimate the risk for myocardial infarction(MI),ischemic stroke(IS),and mortality.RESULTS During a 3.9-year follow-up of 2105228 patients,36003(1.7%)MIs,46496(2.2%)ISs,and 73549(3.5%)deaths were documented.Both longer diabetes duration and lower eGFR were independently associated with higher risks of MI,IS,and mortality,which were further amplified when these factors coexisted.Even patients with new-onset diabetes had elevated MI and IS risk at mildly reduced eGFR(60–90 mL/min/1.73 m^(2)).Mortality risk rose appreciably once eGFR declined below 60 mL/min/1.73 m^(2),particularly in those with longer diabetes duration.eGFR≥90 mL/min/1.73 m2 subgroups had higher death risk than eGFR 60–90 mL/min/1.73 m2 subgroups regardless of diabetic duration.CONCLUSION Increasing diabetes duration and decreasing eGFR are associated with increased risk of MI,IS,and mortality.For cardiovascular risk estimation,diabetes duration should be considered an important risk factor.
文摘1|Introduction Climate change is one of the most significant and widespread global issues,contributing to emerging infectious diseases and threatening human physical and mental health[1,2].Bangladesh,one of the most densely populated countries in South Asia,experiences unpredictable weather and a steady increase in temperature and precipitation.Between 1901 and 2019,Bangladesh saw an average temperature increase of 0.5℃ according to the change in mean monthly temperatures.Warming is more pronounced in winter months,such as January(from 0.6℃ to 1.9℃)and November(1.3℃ to 1.8℃),compared to smaller increase during the monsoon(Figure 1).This reflects uneven seasonal warming,driven by climate change,with winter and pre-winter months experiencing the most significant temperature rises.
文摘Biomass models to estimate carbon stocks in arid environment are very limited. This study employed destructive sampling to develop a new biomass model for Vachellia tortilis, a widely known species in the Sultanate of Oman. Twenty trees with a diameter at stump height (DSH) ranging from 18.5 cm to 150 cm were selected based on DSH and height variations for destructive sampling in As Saleel Natural Park Reserve (SNPR) in Al Sharqiyah governorate, South of Oman. Each tree was excavated and cut into three parts: Stems, Branches, twigs, and leaves. The total fresh weight of each tree was obtained in the field using a 300 balance. Sub-samples (250 - 300 grams) were taken from each part of the tree and transferred to the laboratory for dry weight determination. Linear multiple regression analysis was done using SPSS software between the three variables, DSH, H, CA (x) and the total dry biomass (y). Five models were tested for the best-fit model based on R-Square and Mean Square Error (MSE). Model 5 was the best-fit model, including the LOG of DSH and the LOG of CA (R2 = 0.97, MSE = 0.114). The models developed in this research fill a critical gap in estimating the AGB of terrestrial native species in Oman and other countries with similar ecological and climate conditions.
基金Supported by National Research Foundation of Korea(NRF)grant funded by the Korean Government(MSIT),No.RS-2023-00217317Chonnam National University Grant,No.2024-0444-01and Chonnam National University Hospital Institute for Biomedical Science,No.BCRI24032.
文摘BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship between exercise intensity,DM duration,and ESRD incidence.METHODS This retrospective cohort study analyzed data from 2495031 individuals with DM who underwent the Korean National Health Screening between 2015 and 2016,with follow-up through 2022.The Cox proportional hazards model was adjusted for confounders,including age,sex,income,smoking,and baseline comorbidities.RESULTS Longer DM duration was associated with a significantly higher risk of ESRD,with durations≥10 years showing the highest risk[hazard ratio(HR):2.624,95%confidence interval(CI):2.486-2.770].Increased exercise intensity reduced the risk of developing ESRD across all diabetes duration groups,with the highest exercise category(≥1500 metabolic equivalents of task-min/week)demonstrating a protective effect compared to that of no exercise(HR:0.837,95%CI:0.791-0.886).Exercise benefits were more pronounced in patients without hypertension,non-smokers,and those with lower alcohol consumption.Additionally,ESRD risk reduction was significant among patients with a body mass index≥25 and those without proteinuria or chronic kidney disease.CONCLUSION Longer diabetes duration is associated with increased ESRD risk,while high-intensity exercise may mitigate this risk.These findings suggest promoting exercise is important for managing diabetes to reduce renal complications.
基金supported by the Competitive Research Fund of the University of Aizu,Japan(Grant No.P-13).
文摘Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.
基金Supported by the National Research Foundation(NRF)of Korea,No.RS-2023-00217317。
文摘BACKGROUND Diabetes is a significant risk factor for chronic kidney disease,and diabetic kidney disease(DKD)is prevalent among patients with diabetes.Previous studies have indicated that the duration of diabetes and poor glycemic control are associated with an increased risk of DKD,but data on how the duration and severity of hyperglycemia specifically relate to DKD progression are limited.AIM To investigate the relationship between diabetes duration and glycemic control,and DKD progression in South Korea.METHODS We included 2303 patients with diabetes using the 2019-2021 Korea National Health and Nutrition Examination Surveys data.DKD was defined as an estimated glomerular filtration rate(eGFR)<60 mL/min per 1.73 m2,urinary albumin-to-creatinine ratio≥30 mg/g,or both.Diabetes duration and severity were classified into six categories each.RESULTS DKD prevalence was 25.5%.The DKD risk significantly increased in diabetes lasting 10-15 years or hemoglobin A1C(HbA1c)≥8%compared to patients with newly diagnosed diabetes or HbA1c<6.5%.Albuminuria developed with shorter diabetes duration and lower HbA1c than eGFR decline.The adjusted odds ratios for DKD were 3.77[95%confidence interval(95%CI):2.60-5.45]and 4.91(95%CI:2.80-8.63)in patients with diabetes lasting≥20 years and HbA1c≥10%,respectively,compared to those with new-onset diabetes and HgA1c<6.5%.CONCLUSION Patients with diabetes lasting>10 years or HbA1c>8%had a higher risk of DKD,emphasizing the importance of early monitoring and management is crucial to prevent DKD progression.
文摘Objective:Cardiopulmonary resuscitation(CPR)is one of the most important life-saving procedures in the hospital.Contrary to medical guidelines,family presence during CPR is still not accepted in some countries.Family presence during CPR depends on the nurses’attitude,which is influenced by various factors.Emotional intelligence(EI)helps nurses make wise decisions and display responsible behavior,which is necessary for proper and good performance in nursing.The study’s purpose was to determine the attitude of acute care nurses toward family presence during CPR and its relationship with EI.Methods:The descriptive-analytical study was conducted among the nurses of acute care units(intensive care unit[ICU],critical care unit,and emergency department)in teaching hospitals of Qazvin University of Medical Sciences,Iran,in 2022-2023.A total of 186 nurses were included in the study using convenience sampling.The data collection tools were a checklist of demographic characteristics,nurses’attitude toward the presence of family scale,and Siberia Schering’s EI questionnaire.The collected data were analyzed using descriptive and analytical statistics and SPSS software.Results:The mean age of the participants was(32.05±6.93)years.Of 186 nurses participating in the study,127(68.3%)were women and the rest were men.The mean score of attitude was 47.41±9.41(the minimum score of the nurses was 19 and the maximum score was 95).The mean score of EI was 99.27±8.86(the minimum score was 69 and the maximum score was 128).The results of Pearson’s correlation coefficient showed no significant relationship between the total score of attitude and EI of the participants(P=0.588).Data analysis showed that only the self-arousal dimension of EI has a significant relationship with the range of family self-control behaviors in attitude(P=0.037).Conclusions:The results showed that the nurses of acute care units have a positive attitude toward the presence of the family during CPR and have high EI.Although no significant relationship was observed between the 2 variables,paying attention to the influencing factors on the attitude of the nurse toward family presence during CPR in different societies needs more research and investigation.
