Facilitated Prediction of Micropollutant Degradation via UV-AOPs in Various Waters by Combining Model Simulation and Portable Measurement

The degradation of micropollutants in water via ultraviolet(UV)-based advanced oxidation processes(AOPs)is strongly dependent on the water matrix.Various reactive radicals(RRs)formed in UV-AOPs have different reaction selectivities toward water matrices and degradation efficiencies for target micropollutants.Hence,process selection and optimization are crucial.This study developed a facilitated prediction method for the photon fluence-based rate constant for micropollutant degradation(K′_(p,MP))in various UV-AOPs by combining model simulation with portable measurement.Portable methods for measuring the scavenging capacities of the principal RRs(RRSCs)involved in UV-AOPs(i.e.,HO^(·),SO_(4)^(·-),and Cl^(·))using a mini-fluidic photoreaction system were proposed.The simulation models consisted of photochemical,quantitative structure–activity relationship,and radical concentration steady-state approximation models.The RRSCs were determined in eight test waters,and a higher RRSC was found to be associated with a more complex water matrix.Then,by taking sulfamethazine,caffeine,and carbamazepine as model micropollutants,the k′_(p,MP) values in various UV-AOPs were predicted and further verified experimentally.A lower k′_(p,MP) was found to be associated with a higher RRSC for a stronger RR competition;for example,k′_(p,MP) values of 130.9 and 332.5 m^(2) einstein^(–1),respectively,were obtained for carbamazepine degradation by UV/H_(2)O_(2) in the raw water(RRSC=9.47×10^(4) s^(-1))and sand-filtered effluent(RRSC=2.87×10^(4) s^(-1))of a drinking water treatment plant.The developed method facilitates process selection and optimization for UV-AOPs,which is essential for increasing the efficiency and cost-effectiveness of water treatment.

Human induced dryland degradation in Ordos Plateau,China,revealed by multilevel statistical modeling of normalized difference vegetation index and rainfall time-series

Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.

Reliability Evaluation and Sensitivity Analysis for Multi-state System Based on Time Degradation Measures

The performance and state of multi-state system depend on its structure and different state combinations of the components. In order to evaluate the reliability of multi-state system effectively,a reliability evaluation and sensitivity analysis method based on the time degradation measures was proposed. The equivalence sets of the multi-state system under different output performances were established. The state combinations were classified according to the performance level. The degradation probability models under different states were established,and the new reliability measures,such as dynamic probability of multi-state system,holding time in each state,dynamic expectation function and integrated expectation function of the performance,were proposed and used to implement the dynamic reliability evaluation and sensitivity analysis. A certain diesel engine fuel feeding system was taken as an application example to illustrate the proposed method. The results show that not only the holding time in the desired state of the components and the system can be predicted,but also the best state component in a certain time period can be obtained.

Nonlinear Modeling for a Two-Stage Degradation System Based on Nonhomogeneous Poisson Process

The degradation process modeling is one of research hotspots of prognostic and health management(PHM),which can be used to estimate system reliability and remaining useful life(RUL).In order to study system degradation process,cumulative damage model is used for degradation modeling.Assuming that damage increment is Gamma distribution,shock counting subjects to a homogeneous Poisson process(HPP)when degradation process is linear,and shock counting is a non-homogeneous Poisson process(NHPP)when degradation process is nonlinear.A two-stage degradation system is considered in this paper,for which the degradation process is linear in the first stage and the degradation process is nonlinear in the second stage.A nonlinear modeling method for considered system is put forward,and reliability model and remaining useful life model are established.A case study is given to validate the veracities of established models.

Stiffness Degradation Modeling for Composite Wind Turbine Blades Based on Full-Scale Fatigue Testing

In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.

Product reliability assessment based on proportional hazard degradation model

In order to evaluate the reliability of long-lifetime products with degradation data, a new proportional hazard degradation model is proposed. By the similarity between time-degradation data and stress-accelerated lifetime, and the failure rate function of degradation data which is assumed to be proportional to the time covariate, the reliability assessment based on a proportional hazard degradation model is realized. The least squares method is used to estimate the model＇s parameters. Based on the failure rate of the degradation data and the proportion function of the known time, the failure rate and the reliability function under the given time and the predetermined failure threshold can be extrapolated. A long life GaAs laser is selected as a case study and its reliability is evaluated. The results show that the proposed method can accurately describe the degradation process and it is effective for the reliability assessment of long lifetime products.

Unified Degradation Model in Low Gate Voltage Range During Hot-Carrier Stressing of p-MOS Transistors

Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent on gate voltage.For the devices with thicker oxides,saturated drain current degradation has a close relationship with the product of gate current and electron fluence.For small dimensional devices,saturated drain current degradation has a close relationship with the electron fluence.This degradation model is valid for p MOSFETs with 0 25μm channel length and different gate oxide thicknesses.

Application of a Novel Method for Machine Performance Degradation Assessment Based on Gaussian Mixture Model and Logistic Regression

The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.

Artificial woodland degradation in semi-arid agro-pastoral transitional area： conceptual model and status assessment

Planting trees was used as one of cost-effective measures for desertification control in add and semi-add areas of China. Woodland degradation, however, is becoming an inevitable issue in these areas. In this paper, a typical county, Ejin Holo County, Inner Mongolia, China was selected for its assessment of artificial woodland degradation. A conceptual model for woodland degradation was delineated qualitatively based on field sampling survey, and four model-based indicators as humidity index （HI）, vegetation index （NDVI）, soil type （ST） and soil erosion modulus （EM） were screened out and used to a GIS-based method for artificial woodland degradation assessment in this semi-add agro-pastoral transitional area. All the indicator layers were overlaid and desertification assessed using simplified equation with equal weights for each indicators. The assessment results showed that in 336. 09 km^2 of total woodland area, 311.35 km^2 woodland were under degradation, and the area for slight, medium, severe degradation was 78.97, 119.73 and 112.65 km^2, respectively. It was suggested that much attention should be paid on woodland improvement and plant species selection, especially shrub species, before revegetation in similar areas.

Analysis of Ecosystem Degradation Factors in Yuanmou Arid-Hot Valleys Based on Interpretative Structural Model

For ecological restoration and reconstruction of the degraded area, it is an important premise to correctly understand the degradation factors of the ecosystem in the arid-hot valleys. The factors including vegetation degradation, land degradation, arid climate, policy failure, forest fire, rapid population growth, excessive deforestation, overgrazing, steep slope reclamation, economic poverty, engineering construction, lithology, slope, low cultural level, geological hazards, biological disaster, soil properties etc, were selected to study the Yuanmou arid-hot valleys. Based on the interpretative structural model （ISM）, it has found out that the degradation factors of the Yuanmou arid-hot valleys were not at the same level but in a multilevel hierarchical system with internal relations, which pointed out that the degradation mode of the arid-hot valleys was ＂straight （appearance）-penetrating-background＂. Such researches have important directive significance for the restoration and reconstruction of the arid-hot valleys ecosystem.

Immobilized laccase on magnetic nanoparticles for enhanced lignin model compounds degradation

As a natural aromatic polymer,lignin has great potential but limited industrial application due to its complex chemical structure.Among strategies for lignin conversion,biodegradation has attracted promising interest recently in term of efficiency,selectivity and mild condition.In order to overcome the issues of poor stability and non-reusability of enzyme in the biodegradation of lignin,this work explored a protocol of immobilized laccase on magnetic nanoparticles(MNPs)with rough surfaces for enhanced lignin model compounds degradation.Scanning electron microscope with energy dispersive spectrometer(SEM-EDS),flourier transformation infrared spectroscopy(FTIR)and thermal gravimetric analysis(TGA)were utilized to characterize the immobilization of laccase.The results showed a maximum activity recovery of 64.7%towards laccase when it was incubated with MNPs and glutaraldehyde(GA)with concentrations of 6 mg·ml^-1and 7.5 mg·ml^-1for 5 h,respectively.The immobilized laccase showed improved thermal stability and pH tolerance compared with free laccase,and remained more than 80%of its initial activity after 20 days of storage at 4℃.In addition,about 40%residual activity of the laccase remained after 8 times cycles.Gas chromatography–mass spectrometry(GC–MS)was utilized to characterize the products of lignin model compound degradation and activation,and the efficiency of immobilized laccase was calculated to be 1–5 times that of free laccase.It was proposed that the synergistic effect between MNPs and laccase displays an important role in the enhancement of stability and activity in lignin model compound biodegradation.

Kinetic Modelling of Pesticidal Degradation and Micro-bial Growth in Soil

This paper discusses such models for the degradation kinetics of pesticides in soil as the model expressingthe degradation rate as a function of two variables: the pesticide concentration and the number of pesticide-degrading microorganisms, the model expressing the pesticide concentration as an explicit or implicit functionof time, and the model expressing the pesticide loss rate constants as functions of temperature. These modelsmay interpret the degradation curves with an inflection point . A kinetic model describing the growth processesof microbial populations in a closed system is reported as well.

Validation methodology for distribution-based degradation model

Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models＇ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based de qradation models.

Lifetime prediction for tantalum capacitors with multiple degradation measures and particle swarm optimization based grey model

A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization （PSO） was used. Then, the new PSO-GM（1, 2, co） optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.

Kinetic Modelling of Degradation of Organic Compounds in Soils

A set of equations is suggested to describe the kinetics of degradation of organic compounds applied tosoils and the kinetics of growth of the involved microorganisme:where x is the concentration of organic compound at time t, m is the number of forcroorganisms capableof degrading the organic compound at time t, while j, k, f and g are positive constaats. This model cansatisfactorily be used to explain the degradation curve of organic compounds and the growth curve of theinvolved microorganisms.

A Unified Model for the Degradation Kinetics of Pesticides Applied Continually to Soils

This paper deduces a kinetic model for microbial degradation of pesticides in soils:where x is the concentration of pesticide at time t, so the initial concentration of the pesticide, me the initial number of pesticide-degrading microorganisms, M the carrying capacity for the microorganisms, μ the specific growth rate of the microorganisms, and k the rate constant for the pesticide degradation.In periodic applications of pesticides, this model can be used to continuously describe every degradation curve. Whether a lag phase occurs or not, we can obtain the minimum residue of the pesticide (xe):xe=xdexp(-kMr)/[1-exp(-ker) ]where r is the regular time internals between applications, and xd the dosage of the pesticide.

SEFIDROOD RIVER SUB-WATERSHED-DAM-ESTUARY AND DEGRADATION MODEL:A HOLISTIC APPROACH IN IRAN

The major concern of this article is to address the shortcoming and outgoing effects of the human activities on the landscape patterns and their consequences in the Sefidrood River watershed in Iran. A flow of data includes three inputs; each of them belongs to one part of three zones of a fluvial system. The three parts of the Sefidrood River fluvial system include Zone 1,a sub-watershed as degradation modeling site,Zone 2,Sefidrood Dam as dam site,and Zone 3,17km away from the Sefidrood River path to the Caspian Sea as ending point site. The degradation model in the Zone 1 provides a suitable mean for decision support system to decrease the human impacts on each small district. The maximum number for degradation coefficient belongs to the small district with the highest physiographic density,relatively cumulative activities,and a lower figure for the habitat vulnerability. The human degradation impact were not limited to the upstream. The investigation to the Sefidrood Dam and ending point of the Sefidrood River depicts that sedimentation continues as a significant visual impact in the Sefidrood Dam reservoir and the estuary.

Mathematical modeling of drug release from biodegradable polymeric microneedles

Transdermal drug delivery systems have overcome many limitations of other drug administration routes,such as injection pain and first-pass metabolism following oral route,although transdermal drug delivery systems are limited to drugs with low molecular weight.Hence,new emerging technology allowing high molecular weight drug delivery across the skin—known as‘microneedles’—has been developed,which creates microchannels that facilitate drug delivery.In this report,drug-loaded degradable conic microneedles are modeled to characterize the degradation rate and drug release profile.Since a lot of data are available for polylactic acid-co-glycolic acid(PLGA)degradation in the literature,PLGA of various molecular weights-as a biodegradable polymer in the polyester family-is used for modeling and verification of the drug delivery in themicroneedles.The main reaction occurring during polyester degradation is hydrolysis of steric bonds,leading to molecular weight reduction.The acid produced in the degradation has a catalytic effect on the reaction.Changes in water,acid and steric bond concentrations over time and for different radii of microneedles are investigated.To solve the partial and ordinary differential equations simultaneously,finite difference and Runge–Kutta methods are employed,respectively,with the aid of MATLAB.Correlation of the polymer degradation rate with its molecular weight and molecular weight changes versus time are illustrated.Also,drug diffusivity is related to matrix molecular weight.The molecular weight reduction and accumulative drug release within the system are predicted.In order to validate and assess the proposed model,data series of the hydrolytic degradation of aspirin(180.16 Da)-and albumin(66,000 Da)-loaded PLGA(1:1 molar ratio)are used for comparison.The proposed model is in good agreement with experimental data from the literature.Considering diffusion as themain phenomena and autocatalytic effects in the reaction,the drug release profile is predicted.Based on our results for a microneedle containing drug,we are able to estimate drug release rates before fabrication.

Development of diabetic complications and influencing factors among 32653 type 2 diabetes patients:retrospective cohort study using a multi-state Markov

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.

Hot carrier degradation and a new lifetime prediction model in ultra-deep sub-micron pMOSFET

The hot carrier effect （HCE） of an ultra-deep sub-micron p-channel metal–oxide semiconductor field-effect transistor （pMOSFET） is investigated in this paper. Experiments indicate that the generation of positively charged interface states is the predominant mechanism in the case of the ultra-deep sub-micron pMOSFET. The relation of the pMOSFET hot carrier degradation to stress time （t）, channel width （W ）, channel length （L）, and stress voltage （Vd ） is then discussed. Based on the relation, a lifetime prediction model is proposed, which can predict the lifetime of the ultra-deep sub-micron pMOSFET accurately and reflect the influence of the factors on hot carrier degradation directly.