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Accident statistics show that more than 80% of car-to-pedestrian collisions (CPC) occur when pedestrians cross the road. It is very important to establish a finite element model with natural walking posture to study the kinematics and injury mechanism of pedestrians. In this study, a finite element model of six-year-old child pedestrian is developed with detailed anatomical characteristics and posture parameters as specified in Euro NCAP Pedestrian Human Model Certification (TB024). The numerical human body model is validated in total twelve simulations in which the pedestrian is impacted against four generic vehicle models at speeds 30, 40, 50 km/h prescribed in TB024. The Head Impact Time (HIT), Contact Force and the Trajectories of HC, T12 and AC of all twelve simulations are compared with the reference corridors provided by Technical Bulletin 024. The results indicate that the numerical human body model of a six-year-old child can be used to demonstrate the suitability of the sensing system for the range of pedestrian sizes; the timing of system deployment, and the bonnet deflection due to body loading. Furthermore, the model could be a good tool for further research on pedestrian injury mechanism and the development of pedestrian protection devices. [ABSTRACT FROM AUTHOR]

Novel magnetic CoFe2O4-embedded MIL-101(Cr) with tetramethylammonium hydroxide (CoFe2O4/MIL-101T) was prepared through the facile hydrothermal method. Tetramethylammonium hydroxide acts as a template molecule and avoids the recrystallisation of terephthalic acid. The material was applied as the adsorbent in the magnetic solid-phase extraction (MSPE) process coupled with high-performance liquid chromatography to detect the five flame retardants in environmental water samples. Several parameters affecting MSPE efficiency were systematically investigated, such as MIL-101T content, material amount, desorption solvents, adsorption time, solution pH, theoretical maximum enrichment factor (EFmax) and the reusability. Under optimised conditions, good linearities were achieved for five flame retardants with correlation coefficients R2 > 0.9961. The limits of detections for analytes at the signal-to-noise ratio of three were 0.013–0.071 μg·L−1. This method was applied to the analysis of tap, pond, lake and river waters. The recoveries were in the range of 81.5 ± 3.2–107.0 ± 2.3% with the relative standard deviations ranging from 0.11% to 8.66% in four real water samples. The adsorption mechanism was the hydrophobic interaction between the material and the analytes besides pore adsorption action of the material. [ABSTRACT FROM AUTHOR]

Abstract: Magnetic CoFe2O4‐embedded porous graphitic carbon nanocomposites were prepared through a facile solid‐phase thermal reaction with NaCl as a template. The material was applied in the magnetic solid‐phase extraction process coupled with high performance liquid chromatography with a diode array detector to detect the trace fenpropathrin, cyhalothrin, S‐fenvalerate, and bifenthrin in different water samples. The synthesis conditions of nanomaterial including glucose concentration and calcination time on extraction performance for pyrethroid pesticides have been investigated. Different magnetic solid‐phase extraction parameters have been studied, such as the nanomaterial amount, solution pH, eluent types, adsorption time, and the reusability. Under the optimum conditions, good recoveries (80.2–110.9%) were achieved with relative standard deviations of 0.2–5.8%. There are probably hydrophobic interactions and dipole–dipole attractions between nanocomposites and the analytes. [ABSTRACT FROM AUTHOR]

A child head-form is usually used to evaluate the head injury criterion (HIC) in the collision between the child pedestrian head and engine hood according to Chinese standard GB/T 24550-2009. However, intracranial response, such as principal strain and shear strain of brain tissues, cannot be evaluated by using head-form because of its poor bio-fidelity without detailed brain tissues. In this paper, a validated 6-year-old child head finite element (FE) model with detailed brain tissues was used to substitute the head-form to impact engine hood in order to investigate the effects of thickness and material properties of engine hood on head responses (HIC value, principal strain and shear strain). The results showed that the thickness of inner panel and outer panel of engine hood significantly influenced the head responses of 6-year-old child, while the effect of material properties of engine hood was not significant. The thinner engine hood could provide better protection for child pedestrian head. [ABSTRACT FROM AUTHOR]

In this work, novel ternary composite ZIF-67/Ag NPs/NaYF 4 :Yb,Er is synthesized by solvothermal method. The photocatalytic activity of the composite is evaluated by sulfadiazine (SDZ) degradation under simulated sunlight. High elimination efficiency of the composite is 95.4% in 180 min with good reusability and stability. The active species (h + , ·O 2 - and ·OH) are identified. The attack sites and degradation process of SDZ are deeply investigated based on theoretical calculation and liquid chromatography-mass spectrometry analysis. The upconversion mechanism study shows that favorable photocatalytic effectiveness is attributed to the full utilization of sunlight through the energy transfer upconversion process and fluorescence resonance energy transfer. Additionally, the composite is endowed with outstanding light-absorbing qualities and effective photogenerated electron-hole pair separation thanks to the localized surface plasmon resonance effect of Ag nanoparticles. This work can motivate further design of novel photocatalysts with upconversion luminescence performance, which are applied to the removal of sulphonamide antibiotics in the environment., (© 2024 Wiley‐VCH GmbH.)

The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and quantitative evaluation method was investigated to analyze the craniocerebral injury induced by blunt sticks based on convolutional neural network and finite element method. The velocity curve of stick struck and the maximum principal strain of brain tissue (cerebrum, corpus callosum, cerebellum and brainstem) from the finite element simulation were used as the input and output parameters of the convolutional neural network The convolutional neural network was trained and optimized by using the 10-fold cross-validation method. The Mean Absolute Error (MAE), Mean Square Error (MSE), and Goodness of Fit ( R 2 ) of the finally selected convolutional neural network model for the prediction of the maximum principal strain of the cerebrum were 0.084, 0.014, and 0.92, respectively. The predicted results of the maximum principal strain of the corpus callosum were 0.062, 0.007, 0.90, respectively. The predicted results of the maximum principal strain of the cerebellum and brainstem were 0.075, 0.011, and 0.94, respectively. These results show that the research and development of the deep convolutional neural network can quickly and accurately assess the local brain injury caused by the sticks blow, and have important application value for understanding the quantitative evaluation and the brain injury caused by the sticks struck. At the same time, this technology improves the computational efficiency and can provide a basis reference for transforming the current acceleration-based brain injury research into a focus on local brain injury research.