Previous studies done elsewhere have shown that Eucalyptus poles treated with chromated copper arsenate (CCA) can last over 30 years. Kenya is exceptional because in some eco-regions, the Eucalyptus poles’ life span ...Previous studies done elsewhere have shown that Eucalyptus poles treated with chromated copper arsenate (CCA) can last over 30 years. Kenya is exceptional because in some eco-regions, the Eucalyptus poles’ life span has greatly reduced to 5 years. The current study was designed to evaluate wood deteriorating agents of CCA-treated Eucalyptus poles and variability in four eco-regions of Kenya, namely, dryland, coastal, highland and humid lake. A total of 360 Eucalyptus pole samples were used for this experiment. Three CCA treatments were used to treat transmission poles at 20 kg/cm3 fencing posts samples at 6 kg/cm3, and a control group. Results indicated that termites and wood-decay fungi attacks caused wood deterioration in the four eco-regions. The proportion of power transmission pole degradation by wood deteriorating agents varied across eco-regions, between treatments and control and between time after treatments. Dryland eco-regions had the highest termite-related degradation (41.82%) while wood-decay fungi attack was highest in the highland eco-regions (9.20%). Samples treated with 6 kg/cm3 recorded the lowest level of wood deterioration, manifested by minimal superficial termite and wood-decay fungi attack. Samples treated with 20 kg/cm3 were characterized by moderate termite and wood-decay fungi attacks observed around the heartwood region, unlike sapwood. This study concluded that the deterioration of Eucalyptus CCA-treated poles is a question of climatic variability and hence, to increase the poles’ lifespan, CCA treatment should be tailored according to the characteristics of the ecoregion of use. Further investigations will inform the diversity of termites and decay-fungi across different eco-regions.展开更多
Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospe...Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.展开更多
Different from oil and gas production,hydrate reservoirs are shallow and unconsolidated,whose mechanical properties deteriorate with hydrate decomposition.Therefore,the formations will undergo significant subsidence d...Different from oil and gas production,hydrate reservoirs are shallow and unconsolidated,whose mechanical properties deteriorate with hydrate decomposition.Therefore,the formations will undergo significant subsidence during depressurization,which will destroy the original force state of the production well.However,existing research on the stability of oil and gas production wells assumes the formation to be stable,and lacks consideration of the force exerted on the hydrate production well by formation subsidence caused by hydrate decomposition during production.To fill this gap,this paper proposes an analytical method for the dynamic evolution of the stability of hydrate production well considering the effects of hydrate decomposition.Based on the mechanical model of the production well,the basis for stability analysis has been proposed.A multi-field coupling model of the force state of the production well considering the effect of hydrate decomposition and formation subsidence is established,and a solver is developed.The analytical approach is verified by its good agreement with the results from the numerical method.A case study found that the decomposition of hydrate will increase the pulling-down force and reduce the supporting force,which is the main reason for the stability deterioration.The higher the initial hydrate saturation,the larger the reservoir thickness,and the lower the production pressure,the worse the stability or even instability.This work can provide a theoretical reference for the stability maintaining of the production well.展开更多
Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences...Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.展开更多
Currently,energy conservation draws wide attention in industrial manufacturing systems.In recent years,many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as...Currently,energy conservation draws wide attention in industrial manufacturing systems.In recent years,many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach.This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects.In it,the real processing time of jobs is calculated by using their processing speed and normal processing time.To describe this problem in a mathematical way,amultiobjective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated.Furthermore,we develop a multi-objective multi-verse optimization combined with a stochastic simulation method to deal with it.In this approach,the multi-verse optimization is adopted to find favorable solutions from the huge solution domain,while the stochastic simulation method is employed to assess them.By conducting comparison experiments on test problems,it can be verified that the developed approach has better performance in coping with the considered problem,compared to two classic multi-objective evolutionary algorithms.展开更多
Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracer...Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.展开更多
The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the settin...The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.展开更多
Commercial sterility does not guarantee the sustained stability of ultrahigh temperature(UHT)milk over 6 months shelf life.We explore the microbiota presented in normal(SZ)and quality deteriorated UHT milk(QY and WY)p...Commercial sterility does not guarantee the sustained stability of ultrahigh temperature(UHT)milk over 6 months shelf life.We explore the microbiota presented in normal(SZ)and quality deteriorated UHT milk(QY and WY)products from the same brand.Based on high-throughput sequencing research results,11 phyla and 54 genera were identified as dominant microbiota.Pseudomonas,Streptococcus,and Acinetobacter as core functional microbiota significantly influenced the UHT milk quality properties.Moreover,principal component analysis(PCA)and multivariate analyses were used to examine the quality characteristics,including 11 physicochemical parameters,10 fatty acids,and 2 enzyme activities,in normal and quality deteriorated UHT milk.We found that the abundance of Pseudomonas increased in quality deteriorated milk(WY)and showed a significant positive correlation with heat-resistant protease content.Acinetobacter in quality deteriorated milk(QY)also considerably contributed to the content of heat-resistant lipase,which resulted in spoilage deterioration of UHT milk.展开更多
The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. Th...The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.展开更多
The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fu...The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.展开更多
The shear strength deterioration of bedding planes between different rock types induced by cyclic loading is vital to reasonably evaluate the stability of soft and hard interbedded bedding rock slopes under earthquake...The shear strength deterioration of bedding planes between different rock types induced by cyclic loading is vital to reasonably evaluate the stability of soft and hard interbedded bedding rock slopes under earthquake;however,rare work has been devoted to this subject due to lack of attention.In this study,experimental investigations on shear strength weakening of discontinuities with different joint wall material(DDJM)under cyclic loading were conducted by taking the interface between siltstone and mudstone in the Shaba slope of Yunnan Province,China as research objects.A total of 99 pairs of similar material samples of DDJM(81 pairs)and discontinuities with identical joint wall material(DIJM)(18 pairs)were fabricated by inserting plates,engraved with typical surface morphology obtained by performing three-dimensional laser scanning on natural DDJMs sampled from field,into mold boxes.Cyclic shear tests were conducted on these samples to study their shear strength changes with the cyclic number considering the effects of normal stress,joint surface morphology,shear displacement amplitude and shear rate.The results indicate that the shear stress vs.shear displacement curves under each shear cycle and the peak shear strength vs.cyclic number curves of the studied DDJMs are between those of DIJMs with siltstone and mudstone,while closer to those of DIJMs with mudstone.The peak shear strengths of DDJMs exhibit an initial rapid decline followed by a gradual decrease with the cyclic number and the decrease rate varies from 6%to 55.9%for samples with varied surface morphology under different testing conditions.The normal stress,joint surface morphology,shear displacement amplitude and shear rate collectively influence the shear strength deterioration of DDJM under cyclic shear loading,with the degree of influence being greater for larger normal stress,rougher surface morphology,larger shear displacement amplitude and faster shear rate.展开更多
Objective:To explore the risk factors for the progression of renal function deterioration in patients with diabetic nephropathy(DN).Methods:The clinical data and biochemical indexes of 100 diabetic patients admitted t...Objective:To explore the risk factors for the progression of renal function deterioration in patients with diabetic nephropathy(DN).Methods:The clinical data and biochemical indexes of 100 diabetic patients admitted to our hospital from October 2021 to October 2022 were retrospectively analyzed.The patients were divided into a DN group,which consisted of 55 cases,and a nondiabetic nephropathy group(NDN),which consisted of 45 cases.The urinary microalbumin to creatinine ratio,the clinical data(gender,age,duration of the disease,and BMI),and the biochemical indexes(triglycerides[TG],low-density lipoprotein cholesterol[LDL-C],high-density lipoprotein cholesterol[HDL-C],total cholesterol[TC],glycated hemoglobin A1c[HbA1c],systolic blood pressure[SBP],diastolic blood pressure[DBP])of the two groups were compared.Subsequently,the risk factors related to the progression of renal function deterioration in DN were analyzed through multifactorial logistic regression analysis.Results:No statistically significant difference was observed in the comparison of gender,age,BMI,LDL-C,and DBP between the two groups(P>0.05).The DN group demonstrated a longer disease duration and higher SBP,TC,HDL-C,HbA1c,and TG compared to the NDN group(P<0.05).Through multifactorial logistic regression analysis,it was found that the duration of the disease,the TC,the HDL-C,the HbA1c,the TG,and the SBP were independent risk factors of the deterioration of renal function in DN patients.Conclusion:Other than conventional indicators,TC,HDL-C,HbA1c,TG,and SBP are also crucial indicators in determining the progression of renal function deterioration in DN patients.展开更多
Background:Hospitals have reported that implementing rapid response system activation(RRS)activation has increased patient safety.As a result,there has been growing interest in identifying factors that lead to success...Background:Hospitals have reported that implementing rapid response system activation(RRS)activation has increased patient safety.As a result,there has been growing interest in identifying factors that lead to successful RRS activation.While introducing an automated RRS activation system has prompted nurses to be more vigilant about monitoring vital signs,it has not necessarily encouraged them to conduct thorough patient assessments to identify early signs of deterioration.Purpose:The current study aimed to assess nurses’attitudes towards RRS activation for clinically deteriorated patients in the clinical units of King Abdul-Aziz Hospital.Methods:A descriptive cross-sectional research design was utilised in the study,and 144 nurses working in the medical and surgical units of King Abdul-Aziz Hospital were recruited to participate using a convenient non-probability sampling technique.Results:The study’s findings reported that nurses have a positive attitude towards RRS benefits(Mean=3.70;SD=0.70).Their overall attitude towards RRS activation among clinically deteriorated patients is still low positive(Mean=2.71;SD=0.61).The nurses’attitudes towards RRS benefits significantly differ among nationalities and the clinical area/unit where they were assigned,with a P-value of 0.0194 and 0.000,respectively.Attitudes towards RRS barriers significantly differ among nationality(P-value=0.0037),education level(P-value=0.0032),area of assignment(P-value=0.020),and whether they have a good understanding of abnormal observations(P-value=0.0122).Regarding the nurses’attitude towards management belief,the significant result is only with the clinical area/unit of assignment with a P-value of 0.000.Conclusion:The current study found a low positive attitude towards RRS activation among ward nurses,especially given that monitoring vital signs is critical to their job.Nurses may fear being perceived as clinically inept for redundant activations caused by poor quality,but their attitude towards activating the RRS in clinical deterioration is still largely negative.This is because most RRSs rely on ward nurses to recognise clinical deterioration and manually alert responders through phone calls,hospital communication systems,or face-to-face communication.展开更多
In order to minimize the total cost of the retailer, an optimal replenishment cycle is studied by considering the deteriorating product, two-level trade credits, the limited storage capacity of their own warehouse and...In order to minimize the total cost of the retailer, an optimal replenishment cycle is studied by considering the deteriorating product, two-level trade credits, the limited storage capacity of their own warehouse and credit-linked order quantity simultaneously. A two-echelon supply chain model, which consists of a supplier and a retailer, is established. Then, the retailer＇s optimal replenishment cycle under all the cases are derived by using the optimization theory and method. On the basis of these, the effects of system parameters on the optimal replenishment cycle are examined by using the numerical studies. The results show that, when the retailer＇s trade credit period is longer （shorter） than the customer＇s trade credit period, the optimal replenishment cycle should he increased （decreased） as the retailer＇s trade credit period increases; if the minimum order quantity is high （low）, the optimal replenishment cycle should be increased （not changed） as the minimum order quantity increases.展开更多
A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect main...A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.展开更多
In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimizat...In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimization and maximum lateness minimization corresponding to the first and second special cases of our model under some agreeable conditions. However, corresponding to the third special case of our model, we show that the optimal schedules may be different from those of the classical version for the above objective functions.展开更多
An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reli...An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. A maintenance policy （N） is applied by which the system will be repaired whenever it experiences Nth preventive maintenance （PM）, and an optimal policy （N＊） could be determined numerically or analytically for minimizing the long-run average cost per unit time. Finally, a numerical example is presented to demonstrate the use of this policy.展开更多
Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system rel...Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system reliability caused by the change of the reliability of the component, and seldom considered the joint effect of the probability distribution, improvement rate of the object component. This paper studies the rate of the system reliability upgrading with an improvement of the component reliability for the multi-state consecutive k-out-of-n system. To verify the multi-state consecutive k-out-of-n system reliability upgrading by improving one component based on its improvement rate, an increasing potential importance （IPI） and its physical meaning are described at first. Secondly, the relationship between the IPI and Birnbaum importance measures are discussed. And the IPI for some different improvement actions of the component is further discussed. Thirdly, the characteristics of the IPI are analyzed. Finally, an application to an oil pipeline system is given.展开更多
In the traditional reliability evaluation based on the Bayesian method,the failure probability of nodes is usually expressed by the average failure rate within a period of time.Aiming at the shortcomings of traditiona...In the traditional reliability evaluation based on the Bayesian method,the failure probability of nodes is usually expressed by the average failure rate within a period of time.Aiming at the shortcomings of traditional Bayesian network reliability evaluation methods,this paper proposes a Bayesian network reliability evaluation method considering dynamics and fuzziness.The fuzzy theory and the dynamic of component failure probability are introduced to construct the dynamic fuzzy set function.Based on the solving characteristics of the dynamic fuzzy set and Bayesian network,the fuzzy dynamic probability and fuzzy dynamic importance degree of the fault state of leaf nodes are solved.Finally,through the dynamic fuzzy reliability analysis of CNC machine tool hydraulic system balance circuit,the application of this method in system reliability evaluation is verified,which provides support for fault diagnosis of CNC machine tools.展开更多
This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespa...This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespan and total weighted completion time.Some optimal conditions and algorithms are given and the fact that the problem of total weighted completion times is NP-hard is proved.展开更多
文摘Previous studies done elsewhere have shown that Eucalyptus poles treated with chromated copper arsenate (CCA) can last over 30 years. Kenya is exceptional because in some eco-regions, the Eucalyptus poles’ life span has greatly reduced to 5 years. The current study was designed to evaluate wood deteriorating agents of CCA-treated Eucalyptus poles and variability in four eco-regions of Kenya, namely, dryland, coastal, highland and humid lake. A total of 360 Eucalyptus pole samples were used for this experiment. Three CCA treatments were used to treat transmission poles at 20 kg/cm3 fencing posts samples at 6 kg/cm3, and a control group. Results indicated that termites and wood-decay fungi attacks caused wood deterioration in the four eco-regions. The proportion of power transmission pole degradation by wood deteriorating agents varied across eco-regions, between treatments and control and between time after treatments. Dryland eco-regions had the highest termite-related degradation (41.82%) while wood-decay fungi attack was highest in the highland eco-regions (9.20%). Samples treated with 6 kg/cm3 recorded the lowest level of wood deterioration, manifested by minimal superficial termite and wood-decay fungi attack. Samples treated with 20 kg/cm3 were characterized by moderate termite and wood-decay fungi attacks observed around the heartwood region, unlike sapwood. This study concluded that the deterioration of Eucalyptus CCA-treated poles is a question of climatic variability and hence, to increase the poles’ lifespan, CCA treatment should be tailored according to the characteristics of the ecoregion of use. Further investigations will inform the diversity of termites and decay-fungi across different eco-regions.
基金supported by the National Natural Science Foundation of China(grant No.72074011)the Real World Study Project of Hainan Boao Lecheng Pilot Zone(Real World Study Base of NMPA)(HNLC2022RWS012)+1 种基金the fundamental research funds for central public welfare research institutes(2023CZ-11)National Natural Science Foundation of China(No.82003536).
文摘Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.
基金financially supported by the National Natural Science Foundation of China(Grant No.51890914)。
文摘Different from oil and gas production,hydrate reservoirs are shallow and unconsolidated,whose mechanical properties deteriorate with hydrate decomposition.Therefore,the formations will undergo significant subsidence during depressurization,which will destroy the original force state of the production well.However,existing research on the stability of oil and gas production wells assumes the formation to be stable,and lacks consideration of the force exerted on the hydrate production well by formation subsidence caused by hydrate decomposition during production.To fill this gap,this paper proposes an analytical method for the dynamic evolution of the stability of hydrate production well considering the effects of hydrate decomposition.Based on the mechanical model of the production well,the basis for stability analysis has been proposed.A multi-field coupling model of the force state of the production well considering the effect of hydrate decomposition and formation subsidence is established,and a solver is developed.The analytical approach is verified by its good agreement with the results from the numerical method.A case study found that the decomposition of hydrate will increase the pulling-down force and reduce the supporting force,which is the main reason for the stability deterioration.The higher the initial hydrate saturation,the larger the reservoir thickness,and the lower the production pressure,the worse the stability or even instability.This work can provide a theoretical reference for the stability maintaining of the production well.
文摘Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.
文摘Currently,energy conservation draws wide attention in industrial manufacturing systems.In recent years,many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach.This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects.In it,the real processing time of jobs is calculated by using their processing speed and normal processing time.To describe this problem in a mathematical way,amultiobjective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated.Furthermore,we develop a multi-objective multi-verse optimization combined with a stochastic simulation method to deal with it.In this approach,the multi-verse optimization is adopted to find favorable solutions from the huge solution domain,while the stochastic simulation method is employed to assess them.By conducting comparison experiments on test problems,it can be verified that the developed approach has better performance in coping with the considered problem,compared to two classic multi-objective evolutionary algorithms.
基金Supported by Natural Science Foundation of Shaanxi Province of China(Grant No.2021JM010)Suzhou Municipal Natural Science Foundation of China(Grant Nos.SYG202018,SYG202134).
文摘Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.
文摘The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.
基金supported by the National Natural Science Foundation of China(32172279,31871831)Shenyang Science and Technology Innovation Platform Project(21-103-0-14,21-104-0-28)Shenyang City Youth Science and Technology Innovation Leading Talent Project(RC200495).
文摘Commercial sterility does not guarantee the sustained stability of ultrahigh temperature(UHT)milk over 6 months shelf life.We explore the microbiota presented in normal(SZ)and quality deteriorated UHT milk(QY and WY)products from the same brand.Based on high-throughput sequencing research results,11 phyla and 54 genera were identified as dominant microbiota.Pseudomonas,Streptococcus,and Acinetobacter as core functional microbiota significantly influenced the UHT milk quality properties.Moreover,principal component analysis(PCA)and multivariate analyses were used to examine the quality characteristics,including 11 physicochemical parameters,10 fatty acids,and 2 enzyme activities,in normal and quality deteriorated UHT milk.We found that the abundance of Pseudomonas increased in quality deteriorated milk(WY)and showed a significant positive correlation with heat-resistant protease content.Acinetobacter in quality deteriorated milk(QY)also considerably contributed to the content of heat-resistant lipase,which resulted in spoilage deterioration of UHT milk.
文摘The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.
文摘The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.
基金supported by the National Natural Science Foundation of China(Grant Nos.42377182,52079133 and 41931295).
文摘The shear strength deterioration of bedding planes between different rock types induced by cyclic loading is vital to reasonably evaluate the stability of soft and hard interbedded bedding rock slopes under earthquake;however,rare work has been devoted to this subject due to lack of attention.In this study,experimental investigations on shear strength weakening of discontinuities with different joint wall material(DDJM)under cyclic loading were conducted by taking the interface between siltstone and mudstone in the Shaba slope of Yunnan Province,China as research objects.A total of 99 pairs of similar material samples of DDJM(81 pairs)and discontinuities with identical joint wall material(DIJM)(18 pairs)were fabricated by inserting plates,engraved with typical surface morphology obtained by performing three-dimensional laser scanning on natural DDJMs sampled from field,into mold boxes.Cyclic shear tests were conducted on these samples to study their shear strength changes with the cyclic number considering the effects of normal stress,joint surface morphology,shear displacement amplitude and shear rate.The results indicate that the shear stress vs.shear displacement curves under each shear cycle and the peak shear strength vs.cyclic number curves of the studied DDJMs are between those of DIJMs with siltstone and mudstone,while closer to those of DIJMs with mudstone.The peak shear strengths of DDJMs exhibit an initial rapid decline followed by a gradual decrease with the cyclic number and the decrease rate varies from 6%to 55.9%for samples with varied surface morphology under different testing conditions.The normal stress,joint surface morphology,shear displacement amplitude and shear rate collectively influence the shear strength deterioration of DDJM under cyclic shear loading,with the degree of influence being greater for larger normal stress,rougher surface morphology,larger shear displacement amplitude and faster shear rate.
文摘Objective:To explore the risk factors for the progression of renal function deterioration in patients with diabetic nephropathy(DN).Methods:The clinical data and biochemical indexes of 100 diabetic patients admitted to our hospital from October 2021 to October 2022 were retrospectively analyzed.The patients were divided into a DN group,which consisted of 55 cases,and a nondiabetic nephropathy group(NDN),which consisted of 45 cases.The urinary microalbumin to creatinine ratio,the clinical data(gender,age,duration of the disease,and BMI),and the biochemical indexes(triglycerides[TG],low-density lipoprotein cholesterol[LDL-C],high-density lipoprotein cholesterol[HDL-C],total cholesterol[TC],glycated hemoglobin A1c[HbA1c],systolic blood pressure[SBP],diastolic blood pressure[DBP])of the two groups were compared.Subsequently,the risk factors related to the progression of renal function deterioration in DN were analyzed through multifactorial logistic regression analysis.Results:No statistically significant difference was observed in the comparison of gender,age,BMI,LDL-C,and DBP between the two groups(P>0.05).The DN group demonstrated a longer disease duration and higher SBP,TC,HDL-C,HbA1c,and TG compared to the NDN group(P<0.05).Through multifactorial logistic regression analysis,it was found that the duration of the disease,the TC,the HDL-C,the HbA1c,the TG,and the SBP were independent risk factors of the deterioration of renal function in DN patients.Conclusion:Other than conventional indicators,TC,HDL-C,HbA1c,TG,and SBP are also crucial indicators in determining the progression of renal function deterioration in DN patients.
文摘Background:Hospitals have reported that implementing rapid response system activation(RRS)activation has increased patient safety.As a result,there has been growing interest in identifying factors that lead to successful RRS activation.While introducing an automated RRS activation system has prompted nurses to be more vigilant about monitoring vital signs,it has not necessarily encouraged them to conduct thorough patient assessments to identify early signs of deterioration.Purpose:The current study aimed to assess nurses’attitudes towards RRS activation for clinically deteriorated patients in the clinical units of King Abdul-Aziz Hospital.Methods:A descriptive cross-sectional research design was utilised in the study,and 144 nurses working in the medical and surgical units of King Abdul-Aziz Hospital were recruited to participate using a convenient non-probability sampling technique.Results:The study’s findings reported that nurses have a positive attitude towards RRS benefits(Mean=3.70;SD=0.70).Their overall attitude towards RRS activation among clinically deteriorated patients is still low positive(Mean=2.71;SD=0.61).The nurses’attitudes towards RRS benefits significantly differ among nationalities and the clinical area/unit where they were assigned,with a P-value of 0.0194 and 0.000,respectively.Attitudes towards RRS barriers significantly differ among nationality(P-value=0.0037),education level(P-value=0.0032),area of assignment(P-value=0.020),and whether they have a good understanding of abnormal observations(P-value=0.0122).Regarding the nurses’attitude towards management belief,the significant result is only with the clinical area/unit of assignment with a P-value of 0.000.Conclusion:The current study found a low positive attitude towards RRS activation among ward nurses,especially given that monitoring vital signs is critical to their job.Nurses may fear being perceived as clinically inept for redundant activations caused by poor quality,but their attitude towards activating the RRS in clinical deterioration is still largely negative.This is because most RRSs rely on ward nurses to recognise clinical deterioration and manually alert responders through phone calls,hospital communication systems,or face-to-face communication.
基金The National Natural Science Foundation of China(No.71371003,71001025,71390333)
文摘In order to minimize the total cost of the retailer, an optimal replenishment cycle is studied by considering the deteriorating product, two-level trade credits, the limited storage capacity of their own warehouse and credit-linked order quantity simultaneously. A two-echelon supply chain model, which consists of a supplier and a retailer, is established. Then, the retailer＇s optimal replenishment cycle under all the cases are derived by using the optimization theory and method. On the basis of these, the effects of system parameters on the optimal replenishment cycle are examined by using the numerical studies. The results show that, when the retailer＇s trade credit period is longer （shorter） than the customer＇s trade credit period, the optimal replenishment cycle should he increased （decreased） as the retailer＇s trade credit period increases; if the minimum order quantity is high （low）, the optimal replenishment cycle should be increased （not changed） as the minimum order quantity increases.
基金supported by the National watural Science Foundation of China (60904002)
文摘A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.
文摘In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimization and maximum lateness minimization corresponding to the first and second special cases of our model under some agreeable conditions. However, corresponding to the third special case of our model, we show that the optimal schedules may be different from those of the classical version for the above objective functions.
基金supported by the National Natural Science Foundation of China (60904002)
文摘An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. A maintenance policy （N） is applied by which the system will be repaired whenever it experiences Nth preventive maintenance （PM）, and an optimal policy （N＊） could be determined numerically or analytically for minimizing the long-run average cost per unit time. Finally, a numerical example is presented to demonstrate the use of this policy.
基金supported by the National Natural Science Foundation of China (71271170 71101116)+1 种基金the National High Technology Research and Development Program of China (863 Progrom) (2012AA040914)the Basic Research Foundation of Northwestern Polytechnical University (JC20120228)
文摘Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system reliability caused by the change of the reliability of the component, and seldom considered the joint effect of the probability distribution, improvement rate of the object component. This paper studies the rate of the system reliability upgrading with an improvement of the component reliability for the multi-state consecutive k-out-of-n system. To verify the multi-state consecutive k-out-of-n system reliability upgrading by improving one component based on its improvement rate, an increasing potential importance （IPI） and its physical meaning are described at first. Secondly, the relationship between the IPI and Birnbaum importance measures are discussed. And the IPI for some different improvement actions of the component is further discussed. Thirdly, the characteristics of the IPI are analyzed. Finally, an application to an oil pipeline system is given.
基金This research was supported by the Sichuan Science and Technology Depart-ment under Contract Nos.2019YJ0396 and 2018JY0516the National Natural Science Foundation of China under the Contract No.51705041.
文摘In the traditional reliability evaluation based on the Bayesian method,the failure probability of nodes is usually expressed by the average failure rate within a period of time.Aiming at the shortcomings of traditional Bayesian network reliability evaluation methods,this paper proposes a Bayesian network reliability evaluation method considering dynamics and fuzziness.The fuzzy theory and the dynamic of component failure probability are introduced to construct the dynamic fuzzy set function.Based on the solving characteristics of the dynamic fuzzy set and Bayesian network,the fuzzy dynamic probability and fuzzy dynamic importance degree of the fault state of leaf nodes are solved.Finally,through the dynamic fuzzy reliability analysis of CNC machine tool hydraulic system balance circuit,the application of this method in system reliability evaluation is verified,which provides support for fault diagnosis of CNC machine tools.
文摘This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespan and total weighted completion time.Some optimal conditions and algorithms are given and the fact that the problem of total weighted completion times is NP-hard is proved.
