Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study...Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.展开更多
In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean func...In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean function with the classical kernel estimator,the proposed test statistics are built upon a modified minimum distance between a nonparametric fit and a parametric estimator under the null hypothesis for the variance function.Asymptotic properties of the estimator of the parameters in the variance function are discussed,and the large sample distribution of the test statistics under the null hypothesis is established,as well as the consistency and the power under some local alternative hypotheses.Extensive numerical studies demonstrate that the proposed test procedures have satisfactory finite sample performance.Finally,two real data examples further showcase the effectiveness of the proposed test in real applications.展开更多
As a large family of RNA helicases,DEAD-box(DDX)RNA helicases play crucial roles in almost all cellular RNA processing activities.However,the role of the DDX gene family in cold tolerance of mei(Prunus mume)remains un...As a large family of RNA helicases,DEAD-box(DDX)RNA helicases play crucial roles in almost all cellular RNA processing activities.However,the role of the DDX gene family in cold tolerance of mei(Prunus mume)remains unclear.In this study,we identified 45 DDX genes through whole-genome analysis unevenly distributed across eight chromosomes and scaffolds of mei.Based on the phylogenetic tree and gene structure analysis,the DDX genes were classified into nine subfamilies based on their motif compositions and intron-exon structures.The results of synteny analysis showed that segmental duplication was considered a major factor contributing to the amplification of the PmDDX family.RNA-Seq and qRT-PCR results revealed differential expression of PmDDX genes under cold stress.Among these,PmDDX39 was significantly up-regulated under cold stress,suggesting its positive role in modulating mei cold tolerance.We found that silenced PmDDX39 under cold stress led to greater damage than the wild seedlings via virus-induced gene silencing(VIGS).Conversely,overexpression of PmDDX39 in Arabidopsis enhanced cold stress tolerance.Moreover,dual luciferase and yeast one-hybrid(Y1H)demonstrated that PmDDX39 directly activates the expression of the C-repeat binding factor(PmCBFf)by binding to its promoters.This study provides new insights into the structure,evolution,and functional role of the PmDDX gene family in mei responses to cold stress.展开更多
Background:Os Draconis is an important material in traditional Chinese medicine(TCM).However,its market is saturated with counterfeit products,and the limitations of current identification methods pose a serious threa...Background:Os Draconis is an important material in traditional Chinese medicine(TCM).However,its market is saturated with counterfeit products,and the limitations of current identification methods pose a serious threat to clinical effectiveness and drug safety.This study aims to establish a more accurate and comprehensive authentication system for Os Draconis.Methods:A comprehensive approach was employed to analyze authentic Os Draconis,fossilized Os Draconis,counterfeit products,and lab-prepared modern animal bones.The analytical techniques included ^(14)C dating,electron probe microanalysis(EPMA),polarized light microscopy,X-ray diffraction(XRD),inductively coupled plasma mass spectrometry(ICP-MS),and fourier-transform infrared spectroscopy(FTIR).The study focused on examining the microstructural features and micro-area elemental compositions to identify distinguishing characteristics.Results:Physical identification alone was insufficient to reliably distinguish authentic Os Draconis from its counterfeits.XRD analysis revealed that while hydroxyapatite is the main component in all samples,authentic Os Draconis also contains calcium carbonate and quartz,which were absent in counterfeit and lab-prepared samples.FTIR spectra identified the carbonate ion(CO_(3)^(2-))as a characteristic infrared marker for authentic Os Draconis.ICP-MS analysis showed that Ca and P are the major elements,with a notably high content of Lanthanum(La)among rare earth elements in authentic samples.The EPMA results demonstrated that the Ca/P ratio of authentic Os Draconis is distinct,falling between that of fossilized Os Draconis and counterfeit samples.Conclusion:This study successfully identified several precise markers,including the presence of calcium carbonate,the characteristic CO_(3)^(2-)infrared peak,a high La content,and a specific Ca/P ratio,for the accurate and rapid authentication of Os Draconis.Furthermore,the analysis of its natural porous structure,suitable pore size,and surface area suggests that Os Draconis has significant potential as a natural drug carrier.展开更多
Objective:This study aimed to evaluate the associations of baseline income,cumulative income exposure,and income volatility with the incidence of pancreatic and biliary tract cancers in a nationwide Korean cohort.Meth...Objective:This study aimed to evaluate the associations of baseline income,cumulative income exposure,and income volatility with the incidence of pancreatic and biliary tract cancers in a nationwide Korean cohort.Methods:We analyzed 3,361,091 adults aged 30-65 years who underwent the 2012 National Health Insurance Service(NHIS)health screening.Income level was derived from insurance premium data assessed over the five years preceding baseline(2008-2012)and categorized into baseline income quartiles,cumulative exposure to low or high income,and income volatility based on annual percentage changes.Incident pancreatic and biliary tract cancers were identified using diagnostic codes and the copayment reduction registry.Associations were evaluated using Cox proportional hazards models with adjustment for demographic,lifestyle,and clinical covariates,and cumulative incidence was compared using Kaplan-Meier curves.Results:During a median follow-up of 9.6 years,14,469 pancreatic cancers and 6,647 biliary tract cancers were newly diagnosed.Lower baseline income was associated with a higher risk of pancreatic and biliary tract cancers,whereas sustained high-income exposure was associated with reduced risk.Cumulative low-income exposure showed a positive linear trend with pancreatic cancer incidence.Income volatility was modestly associated with pancreatic cancer and was positively associated with biliary tract cancer in the fully adjusted model.These associations were generally consistent across subgroups,with a stronger inverse association between prolonged high-income exposure and pancreatic cancer among individuals without diabetes.Conclusions:Income level and income stability were significantly associated with the incidence of pancreatic and biliary tract cancers.Lower baseline income was associated with higher risk,whereas sustained high-income exposure was protective.Income volatility was associated with increased cancer risk,particularly for biliary tract cancer.These findings highlight the importance of incorporating income dynamics into cancer prevention strategies and addressing socioeconomic instability among vulnerable populations.展开更多
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
Rock classification plays a crucial role in various fields such as geology,engineering,and environmental studies.Employing deep learning AI(artificial intelligence)methods has a high potential to significantly improve...Rock classification plays a crucial role in various fields such as geology,engineering,and environmental studies.Employing deep learning AI(artificial intelligence)methods has a high potential to significantly improve the accuracy and efficiency of this task.The paper delves into the exploration of two cuttingedge AI techniques,namely Mask DINO and Mask R-CNN(convolutional neural network),as means to identify rock weathering grades and rock types.The results demonstrate that Mask DINO,which is a Detection Transformer(DETR),outperforms Mask R-CNN for the aforementioned purposes.Mask DINO achieved f-1 scores of 91% and 86% in weathering grade detection and rock type detection,as opposed to the Mask R-CNN's f-1 scores of 84% and 75%,respectively.These findings underscore the substantial potential of employing DETR algorithms like Mask DINO for automatic classification of both rock type and weathering states.Although the study examines only two AI models,the data processing and other techniques developed in this study may serve as a foundation for future advancements in the field.By incorporating these advanced AI techniques,logging personnel can obtain valuable references to aid their work,ultimately contributing to the advancement of geological and related fields.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
Objective:This study aimed to evaluate the cost–effectiveness of durvalumab combined with tremelimumab versus sorafenib as the first-line treatment for advanced unresectable hepatocellular carcinoma(uHCC)from the per...Objective:This study aimed to evaluate the cost–effectiveness of durvalumab combined with tremelimumab versus sorafenib as the first-line treatment for advanced unresectable hepatocellular carcinoma(uHCC)from the perspective of China’s healthcare system.Methods:Utilizing data from the HIMALAYA clinical trial,a partitioned survival model was developed to simulate clinical pathways,costs,and outcomes.Incremental cost‒effectiveness ratios(ICERs)were calculated through cost‒utility analysis,with robustness assessed via one-way and probabilistic sensitivity analyses.Results:Total costs for the durvalumab‒tremelimumab regimen reached 152,729.04 USD(1.96 quality-adjusted life years,QALYs),whereas they reached 147,406.75 USD(1.48 QALYs)for sorafenib.The ICER of 11,027.79 USD per QALY remained substantially below China’s willingness-to-pay(WTP)threshold of 36,622.13 USD per QALY.Sensitivity analyses confirmed tremelimumab pricing and discount rates as primary determinants of cost‒effectiveness.Conclusion:Within China’s healthcare framework,durvalumab‒tremelimumab is cost effective as a first-line therapy for uHCC,contingent on formulary inclusion and price adjustments.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
基金supported by the Iran National Science Foundation(INSF)the University of Birjand under grant number 4034771.
文摘Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.
基金supported by the National Natural Science Foundation of China under Grant No.12071267。
文摘In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean function with the classical kernel estimator,the proposed test statistics are built upon a modified minimum distance between a nonparametric fit and a parametric estimator under the null hypothesis for the variance function.Asymptotic properties of the estimator of the parameters in the variance function are discussed,and the large sample distribution of the test statistics under the null hypothesis is established,as well as the consistency and the power under some local alternative hypotheses.Extensive numerical studies demonstrate that the proposed test procedures have satisfactory finite sample performance.Finally,two real data examples further showcase the effectiveness of the proposed test in real applications.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.QNTD202503)Forestry and Grassland Science and Technology Innovation Youth Top Talent Project of China(Grant No.2020132608)Beijing High-Precision Discipline Project,Discipline of Ecological Environment of Urban and Rural Human Settlements.
文摘As a large family of RNA helicases,DEAD-box(DDX)RNA helicases play crucial roles in almost all cellular RNA processing activities.However,the role of the DDX gene family in cold tolerance of mei(Prunus mume)remains unclear.In this study,we identified 45 DDX genes through whole-genome analysis unevenly distributed across eight chromosomes and scaffolds of mei.Based on the phylogenetic tree and gene structure analysis,the DDX genes were classified into nine subfamilies based on their motif compositions and intron-exon structures.The results of synteny analysis showed that segmental duplication was considered a major factor contributing to the amplification of the PmDDX family.RNA-Seq and qRT-PCR results revealed differential expression of PmDDX genes under cold stress.Among these,PmDDX39 was significantly up-regulated under cold stress,suggesting its positive role in modulating mei cold tolerance.We found that silenced PmDDX39 under cold stress led to greater damage than the wild seedlings via virus-induced gene silencing(VIGS).Conversely,overexpression of PmDDX39 in Arabidopsis enhanced cold stress tolerance.Moreover,dual luciferase and yeast one-hybrid(Y1H)demonstrated that PmDDX39 directly activates the expression of the C-repeat binding factor(PmCBFf)by binding to its promoters.This study provides new insights into the structure,evolution,and functional role of the PmDDX gene family in mei responses to cold stress.
基金supported by the Scientific and Technological Innovation Project of the China Academy of Chinese Medical Sciences(CI2021A04013)the National Natural Science Foundation of China(82204610)+1 种基金the Qihang Talent Program(L2022046)the Fundamental Research Funds for the Central Public Welfare Research Institutes(ZZ15-YQ-041 and L2021029).
文摘Background:Os Draconis is an important material in traditional Chinese medicine(TCM).However,its market is saturated with counterfeit products,and the limitations of current identification methods pose a serious threat to clinical effectiveness and drug safety.This study aims to establish a more accurate and comprehensive authentication system for Os Draconis.Methods:A comprehensive approach was employed to analyze authentic Os Draconis,fossilized Os Draconis,counterfeit products,and lab-prepared modern animal bones.The analytical techniques included ^(14)C dating,electron probe microanalysis(EPMA),polarized light microscopy,X-ray diffraction(XRD),inductively coupled plasma mass spectrometry(ICP-MS),and fourier-transform infrared spectroscopy(FTIR).The study focused on examining the microstructural features and micro-area elemental compositions to identify distinguishing characteristics.Results:Physical identification alone was insufficient to reliably distinguish authentic Os Draconis from its counterfeits.XRD analysis revealed that while hydroxyapatite is the main component in all samples,authentic Os Draconis also contains calcium carbonate and quartz,which were absent in counterfeit and lab-prepared samples.FTIR spectra identified the carbonate ion(CO_(3)^(2-))as a characteristic infrared marker for authentic Os Draconis.ICP-MS analysis showed that Ca and P are the major elements,with a notably high content of Lanthanum(La)among rare earth elements in authentic samples.The EPMA results demonstrated that the Ca/P ratio of authentic Os Draconis is distinct,falling between that of fossilized Os Draconis and counterfeit samples.Conclusion:This study successfully identified several precise markers,including the presence of calcium carbonate,the characteristic CO_(3)^(2-)infrared peak,a high La content,and a specific Ca/P ratio,for the accurate and rapid authentication of Os Draconis.Furthermore,the analysis of its natural porous structure,suitable pore size,and surface area suggests that Os Draconis has significant potential as a natural drug carrier.
基金supported and funded by Korea University Guro Hospital(KOREA RESEARCH-DRIVEN HOSPITAL)(No.O2208261)supported by the Korea University Guro Hospital(KOREA RESEARCH-DRIVEN HOSPITAL)+1 种基金grant funded by Korea University Medicine(No.K2313971)by Korea University。
文摘Objective:This study aimed to evaluate the associations of baseline income,cumulative income exposure,and income volatility with the incidence of pancreatic and biliary tract cancers in a nationwide Korean cohort.Methods:We analyzed 3,361,091 adults aged 30-65 years who underwent the 2012 National Health Insurance Service(NHIS)health screening.Income level was derived from insurance premium data assessed over the five years preceding baseline(2008-2012)and categorized into baseline income quartiles,cumulative exposure to low or high income,and income volatility based on annual percentage changes.Incident pancreatic and biliary tract cancers were identified using diagnostic codes and the copayment reduction registry.Associations were evaluated using Cox proportional hazards models with adjustment for demographic,lifestyle,and clinical covariates,and cumulative incidence was compared using Kaplan-Meier curves.Results:During a median follow-up of 9.6 years,14,469 pancreatic cancers and 6,647 biliary tract cancers were newly diagnosed.Lower baseline income was associated with a higher risk of pancreatic and biliary tract cancers,whereas sustained high-income exposure was associated with reduced risk.Cumulative low-income exposure showed a positive linear trend with pancreatic cancer incidence.Income volatility was modestly associated with pancreatic cancer and was positively associated with biliary tract cancer in the fully adjusted model.These associations were generally consistent across subgroups,with a stronger inverse association between prolonged high-income exposure and pancreatic cancer among individuals without diabetes.Conclusions:Income level and income stability were significantly associated with the incidence of pancreatic and biliary tract cancers.Lower baseline income was associated with higher risk,whereas sustained high-income exposure was protective.Income volatility was associated with increased cancer risk,particularly for biliary tract cancer.These findings highlight the importance of incorporating income dynamics into cancer prevention strategies and addressing socioeconomic instability among vulnerable populations.
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.
基金supported by the Construction Industry Council(Grant No.CICR/01/22)the support from the General Research Fund(Grant No.17206822)of the Research Grants Council(Hong Kong).
文摘Rock classification plays a crucial role in various fields such as geology,engineering,and environmental studies.Employing deep learning AI(artificial intelligence)methods has a high potential to significantly improve the accuracy and efficiency of this task.The paper delves into the exploration of two cuttingedge AI techniques,namely Mask DINO and Mask R-CNN(convolutional neural network),as means to identify rock weathering grades and rock types.The results demonstrate that Mask DINO,which is a Detection Transformer(DETR),outperforms Mask R-CNN for the aforementioned purposes.Mask DINO achieved f-1 scores of 91% and 86% in weathering grade detection and rock type detection,as opposed to the Mask R-CNN's f-1 scores of 84% and 75%,respectively.These findings underscore the substantial potential of employing DETR algorithms like Mask DINO for automatic classification of both rock type and weathering states.Although the study examines only two AI models,the data processing and other techniques developed in this study may serve as a foundation for future advancements in the field.By incorporating these advanced AI techniques,logging personnel can obtain valuable references to aid their work,ultimately contributing to the advancement of geological and related fields.
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.
基金supported by the National Natural Science Foundation of China(12231017,72171216,12171449)the National Key R&D Program of China(2022YFA1003803)+1 种基金the Fundamental Research Funds for the Central Universities(WK3470000027)the Innovative Development Funds of Anhui Province Federation of Social Sciences(2022CX081).
文摘Objective:This study aimed to evaluate the cost–effectiveness of durvalumab combined with tremelimumab versus sorafenib as the first-line treatment for advanced unresectable hepatocellular carcinoma(uHCC)from the perspective of China’s healthcare system.Methods:Utilizing data from the HIMALAYA clinical trial,a partitioned survival model was developed to simulate clinical pathways,costs,and outcomes.Incremental cost‒effectiveness ratios(ICERs)were calculated through cost‒utility analysis,with robustness assessed via one-way and probabilistic sensitivity analyses.Results:Total costs for the durvalumab‒tremelimumab regimen reached 152,729.04 USD(1.96 quality-adjusted life years,QALYs),whereas they reached 147,406.75 USD(1.48 QALYs)for sorafenib.The ICER of 11,027.79 USD per QALY remained substantially below China’s willingness-to-pay(WTP)threshold of 36,622.13 USD per QALY.Sensitivity analyses confirmed tremelimumab pricing and discount rates as primary determinants of cost‒effectiveness.Conclusion:Within China’s healthcare framework,durvalumab‒tremelimumab is cost effective as a first-line therapy for uHCC,contingent on formulary inclusion and price adjustments.
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.
