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.

Introducing the nth-Order Features Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (nth-FASAM-N): II. Illustrative Example

This work highlights the unparalleled efficiency of the “nth-Order Function/ Feature Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-FASAM-N) by considering the well-known Nordheim-Fuchs reactor dynamics/safety model. This model describes a short-time self-limiting power excursion in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This nonlinear paradigm model is sufficiently complex to model realistically self-limiting power excursions for short times yet admits closed-form exact expressions for the time-dependent neutron flux, temperature distribution and energy released during the transient power burst. The nth-FASAM-N methodology is compared to the extant “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-CASAM-N) showing that: (i) the 1st-FASAM-N and the 1st-CASAM-N methodologies are equally efficient for computing the first-order sensitivities;each methodology requires a single large-scale computation for solving the “First-Level Adjoint Sensitivity System” (1st-LASS);(ii) the 2nd-FASAM-N methodology is considerably more efficient than the 2nd-CASAM-N methodology for computing the second-order sensitivities since the number of feature-functions is much smaller than the number of primary parameters;specifically for the Nordheim-Fuchs model, the 2nd-FASAM-N methodology requires 2 large-scale computations to obtain all of the exact expressions of the 28 distinct second-order response sensitivities with respect to the model parameters while the 2nd-CASAM-N methodology requires 7 large-scale computations for obtaining these 28 second-order sensitivities;(iii) the 3rd-FASAM-N methodology is even more efficient than the 3rd-CASAM-N methodology: only 2 large-scale computations are needed to obtain the exact expressions of the 84 distinct third-order response sensitivities with respect to the Nordheim-Fuchs model’s parameters when applying the 3rd-FASAM-N methodology, while the application of the 3rd-CASAM-N methodology requires at least 22 large-scale computations for computing the same 84 distinct third-order sensitivities. Together, the nth-FASAM-N and the nth-CASAM-N methodologies are the most practical methodologies for computing response sensitivities of any order comprehensively and accurately, overcoming the curse of dimensionality in sensitivity analysis.

Characteristics of coal resources in China and statistical analysis and preventive measures for coal mine accidents

In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents,this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years(2017-2021),from four dimensions(accident level,type,region,and time),and then proposed the preventive measures based on accident statistical laws.The results show that the storage of coal resources has obvious geographic characteristics,mainly concentrated in the Midwest,with coal resources in Shanxi and Shaanxi accounting for about 49.4%.The proportion of coal consumption has dropped from 70.2%to 56%between 2011 and 2021,but still accounts for more than half of the all.Meanwhile,the accident-prone areas are positively correlated with the amount of coal production.Among different levels of coal mine accidents,general accidents had the highest number of accidents and deaths,with 692 accidents and 783 deaths,accounting for 87.6%and 54.64%respectively.The frequency of roof,gas,and transportation accidents is relatively high,and the number of single fatalities caused by gas accidents is the largest,about 4.18.In terms of geographical distribution of accidents,the safety situation in Shanxi Province is the most severe.From the time distribution of coal mine accidents,the accidents mainly occurred in July and August,and rarely occurred in February and December.Finally,the"4+4"safety management model is proposed,combining the statistical results with coal production in China.Based on the existing health and safety management systems,the manage-ments are divided into four sub-categories,and more specific measures are suggested.

Machine learning applied to road safety modeling:A systematic literature review

Road safety modeling is a valuable strategy for promoting safe mobility,enabling the development of crash prediction models(CPM)and the investigation of factors contributing to crash occurrence.This modeling has traditionally used statistical techniques despite acknowledging the limitations of this kind of approach(specific assumptions and prior definition of the link functions),which provides an opportunity to explore alternatives such as the use of machine learning(ML)techniques.This study reviews papers that used ML techniques for the development of CPM.A systematic literature review protocol was conducted,that resulted in the analysis of papers and their systematization.Three types of models were identified:crash frequency,crash classification by severity,and crash frequency and severity.The first is a regression problem,the second,a classificatory one and the third can be approached either as a combination of the preceding two or as a regression model for the expected number of crashes by severity levels.The main groups of techniques used for these purposes are nearest neighbor classification,decision trees,evolutionary algorithms,support-vector machine,and artificial neural networks.The last one is used in many kinds of approaches given the ability to deal with both regression and classification problems,and also multivariate response models.This paper also presents the main performance metrics used to evaluate the models and compares the results,showing the clear superiority of the ML-based models over the statistical ones.In addition,it identifies the main explanatory variables used in the models,which shows the predominance of road-environmental aspects as the most important factors contributing to crash occurrence.The review fulfilled its objective,identifying the various approaches and the main research characteristics,limitations,and opportunities,and also highlighting the potential of the usage of ML in crash analyses.

Assessing the impact on groundwater safety of inter-basin water transfer using a coupled modeling approach

Surface water and groundwater always behave in a coupled manner and are major components of hydrologic cycle. However, surface water simulation models and groundwater simulation models are run separately most of the time. Few models focus on the impact of hydraulic changes in the surface water flows on the groundwater, or specifically, the impact of a water transfer project to fill a seasonally dry channel. In this study, a linked surface water and groundwater simulation model was developed to assess the impact of a trans-basin water diversion project on the groundwater. A typical plain area east of Beijing was selected as a case study, representing Beijing＇s main source of groundwater used for drinking water. A surface water quality model of the Chaobai River was developed based on the Water Quality Analysis Simulation Program （WASP）, and a groundwater model was developed based on the Modular Finite- Difference Groundwater Flow Model （MODFLOW） and the Modular 3-D transport model （MT3D）. The results of the surface water simulation were used as input for the groundwater simulation. Water levels and four contaminants （NH3-N, CODMn, F, As） were simulated. With the same initial and boundary conditions, scenario analyses were performed to quantify the impact of different quantities of diversion water on the groundwater environment. The results showed the water quality of the groundwater sources was not significantly affected.

Safety modeling and simulation of multi-factor coupling heavy-equipment airdrop

Heavy-equipment airdrop is a highly risky procedure that has a complicated system due to the secluded and complex nature of factors＇ coupling. As a result, it is difficult to study the modeling and safety simulation of this system. The dynamic model of the heavy-equipment airdrop is based on the Lagrange analytical mechanics, which has all the degrees of freedom and can accurately pinpoint the real-time coordinates and attitude of the carrier with its cargo. Unfavorable conditions accounted in the factors＇ models, including aircraft malfunctions and adverse environments, are established from a man-machine-environment perspective. Subsequently, a virtual simulation system for the safety research of the multi-factor coupling heavy-equipment airdrop is developed through MATLAB/Simulink, C language and Flightgear software. To verify the veracity of the theory, the verification model is built based on dynamic software ADAMS. Finally, the emulation is put to the test with the input of realistic accident variables to ascertain its feasibility and validity of this method.

An optimization model for improving highway safety

This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors （CRFs） associated with safety improvement countermeasures, and average daily traffics （ADTs）. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.

Sensitivity Analysis of Geological Parameters Influencing a Solute Transport from a Deep Repository of Spent Nuclear Fuel

When evaluating Nuclear Waste DGR Safety, it is necessary to confirm its safety in a long run and above all its safety towards the biosphere which is more precisely that the biosphere will not be in any hazard caused by radioactive substances, With the aid of geologists, a model of a hypothetical area was elaborated and described with the use of geological and hydrogeological parameters. The volume of isotopes released out of the massif at the borderline of the near/far field from the DGR was determined. The paper results showed that ground water flow and transport of substances within the area were first to be determined. The Flow123D SW was used for the determination. The resulting outcome represents a determination of transported substances concentration depending on time. The disadvantage of the model is the fact that all the input parameters were set deterministically. The problem is solved by using the sensitivity analysis （changing the input parameters） or using the Monte Carlo Method. The major results are： calculations of the radionuclide concentrations in the elements depending on time and determination of parameters that have the biggest impact on the sensitivity of the whole model.

Big Data Interprets US Opioid Crisis

Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids.

Research on Online Safety Precaution Technology of a High-medium Pressure Gas Regulator

In view of some of the characteristics of a high-medium pressure gas regulator, such as small fault samples, many fault types and complex fault features etc, in order to improve the accuracy of fault precaution in this paper, a fault diagnosis method based on the combination of the improved wavelet packet and pressure harmonic distortion rate is proposed. On the basis of the harmonic distortion rate of the outlet pressure and the energy value of each frequency band obtained by improved wavelet packet decomposition, the rules for fault data were summarized. Finally, a safety precaution model of the high-medium pressure gas regulator is established.

Safety Analysis of the Eco-Approach and Departure Application at a Signalized Corridor

Various intelligent transportation systems and strategies for reducing vehicle fuel consumption and emissions have been developed. Energy and emissions could be reduced with the compromise of travel time in some environment-focused Connected Vehicle(CV) applications, which highlighted performance measures in terms of mobility and sustainability. Nevertheless, few studies have focused on safety assessment of such CV applications. In this study, a CV-based eco-driving application, namely, Eco-Approach and Departure(EAD), is selected as an example. A microscopic safety analysis tool, Surrogate Safety Assessment Model(SSAM), is utilized to assess the safety influence of EAD application in multiple scenarios. Further analysis is performed from two perspectives:(1) application users, i.e., EAD-equipped vehicles versus unequipped vehicles; and(2) traffic operators, i.e., overall traffic performance with and without the introduction of EAD. For each perspective, conflict statistics(e.g., frequency, time-to-collision distribution), overall and by type, are analyzed. Results indicate EAD is beneficial in improving the safety performance of equipped vehicles. The influence of EAD on overall traffic is scenario dependent, and a high penetration rate shows positive effects on network-wide safety benefits for most scenarios.

Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model

Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autoregressive（AR） time-series model is improved and adopted to describe the dynamic variations of average daily time headway. Based on the model, a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway. The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China. Finally, a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks.

Influence of geometric design characteristics on safety under heterogeneous traffic flow

This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.

Collision mitigation and vehicle transportation safety using integrated vehicle dynamics control systems

The aim of this paper is to investigate the effect of vehicle dynamics control systems （VDCS） on both the collision of the vehicle body and the kinematic behaviour of the ve- hicle＇s occupant in case of offset frontal vehicle-to-vehicle collision. A unique 6-degree-of- freedom （6-DOF） vehicle dynamics/crash mathematical model and a simplified lumped mass occupant model are developed. The first model is used to define the vehicle body crash parameters and it integrates a vehicle dynamics model with a vehicle front-end structure model. The second model aims to predict the effect of VDCS on the kinematics of the occupant. It is shown from the numerical simulations that the vehicle dynamics/crash response and occupant behaviour can be captured and analysed quickly and accurately. Yurthermore, it is shown that the VDCS can affect the crash characteristics positively and the occupant behaviour is improved.

Cooperative Lane-Change Maneuver for Multiple Automated Vehicles on a Highway

With the development of vehicle-to-vehicle(V2V)communication,it is possible to share information among multiple vehicles.However,the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information.Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency.Therefore,a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed.In these scenarios,same-direction and intersectant-direction cooperative lane changes were defined.The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories,which was called cooperative trajectory planning.The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles,and it essentially developed constraints for the trajectory-planning task.Trajectory planning was treated as an optimization problem with the objective of maximizing safety,comfort,and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model.Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments.Finally,to verify the validity of the proposed maneuver,an integrated simulation platform combining MATLAB/Simulink with CarSim was established.Moreover,a hardware-in-the-loop test bench was performed for further verification.The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.

Analysis method of thermal dam deformation

Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displacement component of the dam caused by single instantaneous temperature variation is obtained.Considering the temporal and spatial distribution law of the ambient temperature and its relation with air and water temperature,the function is expanded into a Taylor series.As a result,the improved thermal displacement component expression for a dam monitoring model is obtained.

Analyses of maximum-speed path definition at single-lane roundabouts

The process of designing roundabouts is an iterative process through which, in several checks, the design elements of a roundabout get optimized. Existing regulations for roundabouts involve swept path analyses, sight distance analyses and speed analyses of vehicles passing through the roundabout. Speed analyses are done mostly based on two models, Dutch and American. Each of these two models, in their own way takes into account design elements of the roundabouts, and the US model also envisions the construction of vehicle paths through the roundabout. Main assumption of both models is that vehicle paths through roundabouts consist of few connected radii. US models for path definition takes into account safety distances from marked lines and geometric elements（curbs） at the entrance and exit and through roundabout. Experimentally determined elements of the vehicle path through the roundabout, do not correspond to those recommendations. Comparison of the measured speed at the roundabouts and speed calculated according to aforementioned models at several roundabouts in Croatia, showed a significant difference. An experimental research was conducted as a first step in developing a new model for operating speed through roundabouts. The research aimed to define the basic path elements of vehicle movement in the roundabout at which the maximum speed is achieved. Results of the study are presented in this paper.