Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Similarity evaluation model for the internal defect detection of strip steel

An internal defect meter is an instrument to detect the internal inclusion defects of cold-rolled strip steel.The detection accuracy of the equipment can be evaluated based on the similarity of the multiple detection data obtained for the same steel coil.Based on the cosine similarity model and eigenvalue matrix model,a comprehensive evaluation method to calculate the weighted average of similarity is proposed.Results show that the new method is consistent with and can even replace artificial evaluation to realize the automatic evaluation of strip defect detection results.

Evaluating Common Land Model Energy Fluxes Using FLUXNET Data

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model(Co LM) over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise(30 min) to monthly. A comparison between the simulations and observations indicated that Co LM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes. A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas Co LM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. Co LM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why Co LM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, Co LM performs best for evergreen broadleaf forests and worst for croplands and wetlands.

Method for Evaluating Bolt Competitive Failure Life Under Composite Excitation

In this study,the competitive failure mechanism of bolt loosening and fatigue is elucidated via competitive failure tests on bolts under composite excitation.Based on the competitive failure mechanism,the mode prediction model and“load ratio-life prediction curve”(ξ-N curve)of the bolt competitive failure are established.Given the poor correlation of theξ-N curve,an evaluation model of the bolt competitive failure life is proposed based on Miner’s linear damage accumulation theory.Based on the force analysis of the thread surface and simulation of the bolt connection under composite excitation,a theoretical equation of the bolt competitive failure life is established to validate the model for evaluating the bolt competitive failure life.The results reveal that the proposed model can accurately predict the competitive failure life of bolts under composite excitation,and thereby,it can provide guidance to engineering applications.

A Dynamic Bayesian-Based Comprehensive Trust Evaluation Model for Dispersed Computing Environment

Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.

Quantitative evaluation model of shale oil adsorption:A case study of the first member of Cretaceous Qingshankou Formation in northern Songliao Basin,NE China

A quantitative evaluation model that integrates kerogen adsorption and clay pore adsorption of shale oil was proposed,and the evaluation charts of adsorption-swelling capacity of kerogen(Mk)and adsorbed oil capacity of clay minerals(Mc)were established,taking the 1st member of Cretaceous Qingshankou Formation in the northern Songliao Basin as an example.The model and charts were derived from swelling oil experiments performed on naturally evolved kerogens and adsorbed oil experiments on clays(separated from shale core samples).They were constructed on the basis of clarifying the control law of kerogen maturity evolution on its adsorption-swelling capacity,and considering the effect of both the clay pore surface area that occupied by adsorbed oil and formation temperature.The results are obtained in four aspects:(1)For the Qing 1 Member shale,with the increase of maturity,Mk decreases.Given Ro of 0.83%–1.65%,Mk is about 50–250 mg/g.(2)The clay in shale adsorbs asphaltene.Mc is 0.63 mg/m^(2),and about 15%of the clay pore surface is occupied by adsorbed oil.(3)In the low to medium maturity stages,the shale oil adsorption is controlled by organic matter.When Ro>1.3%,the shale oil adsorption capacity is contributed by clay pores.(4)The oil adsorption capacity evaluated on the surface at room temperature is 8%–22%(avg.15%)higher than that is held in the formations.The proposed evaluation model reveals the occurrence mechanisms of shale oils with different maturities,and provides a new insight for estimating the reserves of shale oil under formation temperature conditions.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

Establishment and evaluation of a risk prediction model for gestational diabetes mellitus

BACKGROUND Gestational diabetes mellitus(GDM)is a condition characterized by high blood sugar levels during pregnancy.The prevalence of GDM is on the rise globally,and this trend is particularly evident in China,which has emerged as a significant issue impacting the well-being of expectant mothers and their fetuses.Identifying and addressing GDM in a timely manner is crucial for maintaining the health of both expectant mothers and their developing fetuses.Therefore,this study aims to establish a risk prediction model for GDM and explore the effects of serum ferritin,blood glucose,and body mass index(BMI)on the occurrence of GDM.AIM To develop a risk prediction model to analyze factors leading to GDM,and evaluate its efficiency for early prevention.METHODS The clinical data of 406 pregnant women who underwent routine prenatal examination in Fujian Maternity and Child Health Hospital from April 2020 to December 2022 were retrospectively analyzed.According to whether GDM occurred,they were divided into two groups to analyze the related factors affecting GDM.Then,according to the weight of the relevant risk factors,the training set and the verification set were divided at a ratio of 7:3.Subsequently,a risk prediction model was established using logistic regression and random forest models,and the model was evaluated and verified.RESULTS Pre-pregnancy BMI,previous history of GDM or macrosomia,hypertension,hemoglobin(Hb)level,triglyceride level,family history of diabetes,serum ferritin,and fasting blood glucose levels during early pregnancy were determined.These factors were found to have a significant impact on the development of GDM(P<0.05).According to the nomogram model’s prediction of GDM in pregnancy,the area under the curve(AUC)was determined to be 0.883[95%confidence interval(CI):0.846-0.921],and the sensitivity and specificity were 74.1%and 87.6%,respectively.The top five variables in the random forest model for predicting the occurrence of GDM were serum ferritin,fasting blood glucose in early pregnancy,pre-pregnancy BMI,Hb level and triglyceride level.The random forest model achieved an AUC of 0.950(95%CI:0.927-0.973),the sensitivity was 84.8%,and the specificity was 91.4%.The Delong test showed that the AUC value of the random forest model was higher than that of the decision tree model(P<0.05).CONCLUSION The random forest model is superior to the nomogram model in predicting the risk of GDM.This method is helpful for early diagnosis and appropriate intervention of GDM.

Evaluation of Water Resources Carrying Capacity in Gansu Section of Yellow River Basin Based on Fuzzy Comprehensive Evaluation Model

As a basic natural resource and strategic economic resource,the development and utilization of water resources is an important issue related to the national economy and people's livelihood.How to scientifically evaluate the water resources carrying capacity is the premise to improve the regional water resources carrying capacity and ensure the regional water security.The Gansu section of the Yellow River basin is an important water conservation and recharge area.Whether the water resources in this area can ensure the normal operation of the ecosystem and whether it can carry the sustainable development of social economy is the key to realize the high-quality development of the Yellow River basin.In this study,from the three dimensions of water consumption per capita,water consumption of 10000 yuan GDP and ecological water use rate,by constructing the evaluation index system and index grading standard of water resources carrying capacity,the fuzzy comprehensive evaluation model was used to evaluate the water resources carrying capacity of Gansu section of the Yellow River Basin,in order to provide theoretical decision-making basis for the comprehensive development,utilization and planning management of water resources in Gansu section of the Yellow River basin and even the whole basin,and help the high-quality development of the Yellow River basin.

Calculation and Evaluation of Ecological Flow of Hydropower Station Based on Fuzzy Evaluation Model

The reasonable determination of ecological flow is of great significance for the efforts to promote the transformation of water ecological environmental protection from pollution management to synergistic management of water resources,water ecology and water environment,and to promote them in an integrated manner.This paper analyzed and calculated the ecological flow process of the Bangsha River diversion power station using the minimum ecological flow method,the annual spreading method,the improved annual spreading method,the NGPRP method,and the month-by-month frequency method,and evaluated the reasonableness of the process and results of the ecological flow calculations by using the fuzzy evaluation model established.The study showed that the minimum ecological flow rate determined by improving the coupling of the spreading method and the NGPRP method was the best,and the suitable ecological flow rate determined by the month-by-month frequency method was the best;the minimum ecological flow rate of the Bangsha River diversion power station was at 0.43-4.21 m 3/s,and the suitable ecological flow rate was at 0.56-4.94 m 3/s,and the trend of its change showed the trend of first increasing and then decreasing,and the trend of change from January to July showed the trend of first increasing and then decreasing.Its trend of change showed an increasing and then decreasing trend,from January to July showed a gradually increasing trend,from August to December showed a gradually decreasing trend.It aimed to provide a theoretical basis for the reasonable determination of the ecological flow of the river hydropower station.

A data assimilation-based forecast model of outer radiation belt electron fluxes

Because radiation belt electrons can pose a potential threat to the safety of satellites orbiting in space,it is of great importance to develop a reliable model that can predict the highly dynamic variations in outer radiation belt electron fluxes.In the present study,we develop a forecast model of radiation belt electron fluxes based on the data assimilation method,in terms of Van Allen Probe measurements combined with three-dimensional radiation belt numerical simulations.Our forecast model can cover the entire outer radiation belt with a high temporal resolution(1 hour)and a spatial resolution of 0.25 L over a wide range of both electron energy(0.1-5.0 MeV)and pitch angle(5°-90°).On the basis of this model,we forecast hourly electron fluxes for the next 1,2,and 3 days during an intense geomagnetic storm and evaluate the corresponding prediction performance.Our model can reasonably predict the stormtime evolution of radiation belt electrons with high prediction efficiency(up to~0.8-1).The best prediction performance is found for~0.3-3 MeV electrons at L=~3.25-4.5,which extends to higher L and lower energies with increasing pitch angle.Our results demonstrate that the forecast model developed can be a powerful tool to predict the spatiotemporal changes in outer radiation belt electron fluxes,and the model has both scientific significance and practical implications.

Research on the Construction of Evaluation Model for the Development of Biopharmaceutical Park in China

Objective To study the influencing factors on the development of biopharmaceutical park,and to construct an evaluation model of the influencing factors for biopharmaceutical park in China.Methods By analyzing various factors affecting biopharmaceutical parks,an evaluation index system of biopharmaceutical parks and an evaluation model of influencing factors of biopharmaceutical park development based on fuzzy group decision making were established.Results and Conclusion Factors such as research and development(R&D)funding investment,incentive for transformation of scientific and technological achievements,and industrial clusters have a greater impact on the development of biopharmaceutical industrial parks in China.Local governments should increase the investment in R&D funding.Besides,they should pay attention to the incentive of transformation of scientific and technological achievements to improve the innovation ability of enterprises.Meanwhile,they should promote the clustering of high-tech enterprises to comprehensively enhance the healthy development of biopharmaceutical parks in China.

Evaluation model of landslide hazards induced by the 2008 Wenchuan earthquake using strong motion data

Landslides induced by the 2008 Wenchuan earthquake in the Longmenshan area were relatively well instrumented,which makes it possible to investigate the landslides using ground motion records.Firstly,this paper analyzes the data from Wenchuan earthquake on both regional and local site scale.The analyses show that the Newmark accumulative displacement calculated from the ground motion recorded in a particular geological hazard zone corresponds to the hazard intensity in that zone;the larger the displacement,the more serious the geologic hazard.The calculated result also shows that the displacement is related to the Arias intensity,which represents the total energy released during the earthquake at the observation site.Secondly,this paper constructs an evaluation model of Newmark displacement calculated with Arias intensities to estimate the subsequent slope failure resulting from the earthquake.The calculated results based on the model fit well with the distribution of actual landslides,suggesting that this method is useful for hazard evaluation.Therefore,this type of model can be used for estimating regional-scale distribution of earthquake-induced landslides and their associated hazards immediately after an earthquake.

Evaluation of Arctic Sea Ice Drift and its Relationship with Near-surface Wind and Ocean Current in Nine CMIP6 Models from China

The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.

Evaluaton model for the geometry complexity of casting based on fuzzy theory

The parameters that describe the complex degree of a certain casting are of some uncertainty. Therefore, a new method based on the fuzzy theory to classify the complex degree of castings has been presented in this paper. The feasibility of fuzzy theory in describing the complex degree of castings has been discussed and the procedure of this method has been specified by analyzing the complex degrees of some typical castings. The element factors that influence the casting complexity, have been summarized, which include the wall-thickness and the number of transition surface, etc. The results show that it is reasonable and practicable to classify the complex degree of castings with the fuzzy theory.

Model of Security Evaluation of Infrastructure as a Service Layer of Cloud Computing System

At present,most providers of cloud computing mainly provide infrastructures and services of infrastructure as a service(IaaS).But there is a serious problem that is the lack of security standards and evaluation model of IaaS.After analyzing the vulnerabilities performance of IaaS cloud computing system,the mapping relationship was established between the vulnerabilities of IaaS and the nine threats of cloud computing which was released by cloud security alliance(CSA).According to the mapping relationship,a model for evaluating security of IaaS was proposed which verified the effectiveness of the model on OpenStack by the analytic hierarchy process(AHP) and the fuzzy evaluation method.

Evaluation of direct intramural injection to the bladder wall as a method for developing orthotopic tumor models

Background:Bladder cancer poses a great burden on society and its high rate of recurrence and treatment failure necessitates use of appropriate animal models to study its pathogenesis and test novel treatments.Orthotopic models are superior to other types since they provide a normal microenvironment.Four methods are described for developing bladder cancer models inside the animal’s bladder.Direct intramural injection is one of these methods and is widely used.However,its efficacy in model development has not yet been studied.We aimed to evaluate the efficacy and success rate of the direct intramural injection method of developing an orthotopic model for the study of bladder cancer.Method:Tumor cell lines were prepared in four microtubes.Aliquots of 200×10^(3) cells were injected through a 27 gauge needle into the ventral wall of the bladders of 4male and 4 female BALB/c mice following a midline 1 cm laparotomy incision.In addition,1 million cells from each microtube were injected into the flanks of control mice.To prevent infection and alleviate pain,5 mg/kg enrofloxacin and 2.5 mg/kg flunixin meglumine,respectively,were injected subcutaneously.Results:Tumors formed in all mice,resulting in 100% take rate and zero post-operation mortality.Surgery time was≤15 min per mouse.In two mice,tumors were found in the peritoneal space as well.Conclusion:Direct intramural injection is a rapid,reliable,and reproducible method for developing orthotopic models of bladder cancer.It can be done on both male and female mice and only requires readily available surgical tools.However,needle track can result in cell spillage and peritoneal tumors.

MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Model-based optimal design of phase change ionic liquids for efficient thermal energy storage

The selection of phase change material(PCM)plays an important role in developing high-efficient thermal energy storage(TES)processes.Ionic liquids(ILs)or organic salts are thermally stable,non-volatile,and non-flammable.Importantly,researchers have proved that some ILs possess higher latent heat of fusion than conventional PCMs.Despite these attractive characteristics,yet surprisingly,little research has been performed to the systematic selection or structural design of ILs for TES.Besides,most of the existing work is only focused on the latent heat when selecting PCMs.However,one should note that other properties such as heat capacity and thermal conductivity could affect the TES performance as well.In this work,we propose a computer-aided molecular design(CAMD)based method to systematically design IL PCMs for a practical TES process.The effects of different IL properties are simultaneously captured in the IL property models and TES process models.Optimal ILs holding a best compromise of all the properties are identified through the solution of a formulated CAMD problem where the TES performance of the process is maximized.[MPyEtOH][TfO]is found to be the best material and excitingly,the identified top nine ILs all show a higher TES performance than the traditional PCM paraffin wax at 10 h thermal charging time.

Model Transformer Evaluation of High-Permeability Grain-Oriented Electrical Steels

The dependence of transformer performance on the material properties was investigated using two laboratory-processed 0.23 mm thick grain-oriented electrical steels domain-refined with electrolytically etched grooves having different magnetic properties. The iron loss at 1.7 T, 50 Hz and the flux density at 800 A/m of material A were 0.73 W/kg and 1.89 T, respectively, and those of material B, 0.83 W/kg and 1.88 T. Model stacked and wound transformer core experiments using the tested materials exhibited performance well reflecting the material characteristics. In a three-phase stacked core with step-lap joints excited to 1.7 T, 50 Hz, the core loss, the exciting current and the noise level were 0.86 W/kg. 0.74 A and 52 dB, respectively, with material A, and 0.97 W/kg, 1.0 A and 54 dB with material B. The building factors for the core losses of the two materials were almost the same in both core configurations. The effect of higher harmonics on transformer performance was also investigated.