Research Progress of Evaluation Models of Cosmetic Anti-Allergy Safety

YiwenAbstractThe aim of this study was to explore the mechanism of skin allergic reactions,and the role of skin allergic mediators in different types of allergic reactions.Further,we reviewed and classified anti-allergic safety evaluation models of cosmetics based on skin allergic media.In addition,the study explored in vitro experiments,cell experiments and animal experiments performed using anti-allergic safety evaluation model.The findings of this study provide information on the importance of anti-allergic safety evaluation models in cosmetics industry,and guides on selection of anti-allergic raw materials.Moreover,the findings of this study provide a basis for further research on development of mild cosmetics.

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.

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.

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.

Evaluation of CMIP5 Climate Models in Simulating 1979–2005 Oceanic Latent Heat Flux over the Pacific

The climatological mean state, seasonal variation and long-term upward trend of 1979-2005 latent heat flux （LHF） in historical runs of 14 coupled general circulation models from CMIP5 （Coupled Model Intercomparison Project Phase 5） are evaluated against OAFlux （Objectively Analyzed air-sea Fluxes） data. Inter-model diversity of these models in simulating the annual mean climatological LHF is discussed. Results show that the models can capture the climatological LHF fairly well, but the amplitudes are generally overestimated. Model-simulated seasonal variations of LHF match well with observations with overestimated amplitudes. The possible origins of these biases are wind speed biases in the CMIP5 models. Inter-model diversity analysis shows that the overall stronger or weaker LHF over the tropical and subtropical Pacific region, and the meridional variability of LHF, are the two most notable diversities of the CMIP5 models. Regression analysis indicates that the inter-model diversity may come from the diversity of simulated SST and near-surface atmospheric specific humidity. Comparing the observed long-term upward trend, the trends of LHF and wind speed are largely underestimated, while trends of SST and air specific humidity are grossly overestimated, which may be the origins of the model biases in reproducing the trend of LHF.

An evaluation of the simulations of the Arctic Intermediate Water in climate models and reanalyses

The simulations of the Arctic Intermediate Water in four datasets of climate models and reanalyses, CCSM3, CCSM4, SODA and GLORYS, are analyzed and evaluated. The climatological core temperatures and depths in both CCSM models exhibit deviations over 0.5°C and 200 m from the PHC. SODA reanalysis reproduces relatively reasonable spatial patterns of core temperature and depth, while GLORYS, another reanalysis, shows a remarkable cooling and deepening drift compared with the result at the beginning of the dataset especially in the Eurasian Basin （about 2°C）. The heat contents at the depth of intermediate water in the CCSM models are overestimated with large positive errors nearly twice of that in the PHC. To the contrary, the GLORYS in 2009 show a negative error with a similar magnitude, which means the characteristic of the water mass is totally lost. The circulations in the two reanalyses at the depth of intermediate water are more energetic and realistic than those in the CCSMs, which is attributed to the horizontal eddy-permitting reso-lution. The velocity fields and the transports in the Fram Strait are also investigated. The necessity of finer horizontal resolution is concluded again. The northward volume transports are much larger in the two re-analyses, although they are still weak comparing with mooring observations. Finally, an investigation of the impact of assimilation is done with an evidence of the heat input from assimilation. It is thought to be a reason for the good performance in the SODA, while the GLORYS drifts dramatically without assimilation data in the Arctic Ocean.

Establishment and validation of psoriasis evaluation models

Psoriasis is a common inflammatory skin disease that seriously affects the patient's quality of life.The diagnosis of psoriasis is mainly based on clinical and pathological features,and the assessment depends on the psoriasis area and severity index(PASI).However,there are few reliable and accurate evaluation methods to assess lesion severity and therapeutic effects.This work identified 17 model genes from GEO datasets and established 6 psoriasis evaluation models by LASSO regression,linear regression,and random forest separately.Models were trained and evaluated in different GEO datasets.All 6 models accurately classified psoriatic lesions and non-lesional skin in training and testing data,and showed good AUC.In biologics-treated samples,the model scores were positively correlated with the severity of lesions and negatively correlated with treatment length.Thus,models have the potential to assess the therapeutic effects.In addition,the expression of model genes was examined in keratinocytes,skin of IMQ-induced psoriatic mice,and lesions of psoriasis patients.The RNA and protein levels of model genes increased in cytokine-stimulated keratinocytes and psoriatic lesions as expected.This work provides new methods to assess the lesion severity and therapeutic effects of biologies in psoriasis.

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.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

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.

Evaluation of the Eta Simulations Nested in Three Global Climate Models

To provide long-term simulations of climate change at higher resolution, Regional Climate Models (RCMs) are nested in global climate models (GCMs). The objective of this work is to evaluate the Eta RCM simulations driven by three global models, the HadGEM2-ES, BESM, and MIROC5, for the present period, 1961-1990. The RCM domain covers South America, Central America, and Caribbean. These simulations will be used for assessment of climate change projections in the region. Maximum temperatures are generally underestimated in the domain, in particular by MIROC5 driven simulations, in summer and winter seasons. Larger spread among the simulations was found in the minimum temperatures, which showed mixed signs of errors. The spatial correlations of temperature simulations against the CRU observations show better agreement for the MIROC5 driven simulations. The nested simulations underestimate precipitation in large areas over the continent in austral summer, whereas in winter overestimate occurs in southern Amazonia, and underestimate in southern Brazil and eastern coast of Northeast Brazil. The annual cycle of the near-surface temperature is underestimated in all model simulations, in all regions in Brazil, and in most of the year. The temperature and precipitation frequency distributions reveal that the RCM and GCM simulations contain more extreme values than the CRU observations. Evaluations of the climatic extreme indicators show that in general hot days, warm nights, and heat waves are increasing in the period, in agreement with observations. The Eta simulations driven by HadGEM2-ES show wet trends in the period, whereas the Eta driven by BESM and by MIROC5 show trends for drier conditions.

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.

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.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Evaluation of 3D crustal seismic velocity models in southwest China:Model performance,limitation,and prospects

Southwest China is a tectonically and seismically active region,witnessing strong deformation due to the collision between the Indian and Eurasian plates.Constraining the subsurface velocity structure of this region is thus important in understanding the tectonics and geodynamic processes of continental collision and in mitigating seismic hazards.Numerous studies have provided various 3D seismic velocity models in southwest China.However,discrepancies exist among these models,and less effort has been made to quantify the reliability and accuracy of these existing velocity models.In this study,we use regional 3D waveform simulation to evaluate the performance of various regional crustal 3D velocity models in reproducing observed seismograms.We particularly focus on two recent earthquake sequence in the region,the 2021 Yunnan Yangbi MS_(6.4) earthquake sequence and the 2022 Sichuan Luding MS_(6.8) earthquake sequence.The tested 3D velocity models include the Southwest China Community Velocity model V1.0,the Unified Seismic Tomography Models for Continental China Lithosphere V2.0,the adjoint full waveform tomography model of the crustal and upper mantle beneath Eastern Tibetan Plateau,and the shallow seismic structure model beneath continental China.Our results show that the tested 3D velocity models generally capture well long-period(<0.2 Hz)waveforms,indicating that the 3D models adequately resolve overall large-scale subsurface structures.However,the 3D synthetics show discrepancies in higher frequencies(0.05–0.3 Hz)and the performance of the 3D velocity models varies from region to region,suggesting that smaller scale heterogeneities are not well constrained.Including shallow velocity structures(<10 km)can improve the waveform fitting,emphasizing the importance of incorporating shallow structures in waveform modeling.The full-waveform tomography model shows a slighter better performance than the other models,especially for the body-waves,highlighting the advantages of full-waveform method in achieving sub-wavelength resolution despite the usage of very long-period waveforms.In light of these comparison results of model performance,we identify the advantages and limitations of different seismic tomography models and methods,and we propose to incorporate different tomography methods and datasets to better constrain subsurface structures.While our target region in this study is southwest China,the analysis that we have conducted can be applied to other regions of various scales and tectonic settings for quantitative seismic model evaluation.

Assessment of Indices of Temperature Extremes Simulated by Multiple CMIP5 Models over China

Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 （CMIP5） models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity （absolute indices and threshold indices）, duration （duration indices）, and frequency （percentile indices） of extreme temperature. The overall performance of each model is summarized by a ＂portrait＂ diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.