Analysis of Thorax Injuries in 112 Death Cases Caused by Traffic Accidents

Objective: To explore the characteristics and mechanisms of serious injuries of chest caused by road traffic accidents. Methods: Totally 112 autopsy cases with chest injuries in the urban of Jingzhou road traffic accidents were collected. Systematic review and analysis of the general information, postmortem examinations and assessments of chest injury had carried out from Feb. 2016 to Mar. 2018. Results: Average age of the victims was 52.2 years and the ratio of male to female deaths was 2.39:1. The proportion of motor-cyclists and pedestrians increased significantly. The overwhelming majority of accident vehicles were motorcycles and bicycles. Fractures of ribs and pulmonary contusion were the most common injuries. Craniocerebral and abdominal injuries were the most common associated injuries. Conclusion: Fractures of ribs and pulmonary contusion were the most common features of fatal road traffic injuries, often associated with vitreoretinal damage and serious multiple damages. These features reflect the characteristics of great violence in traffic accidents, which provides the evidence of identification of violent injuries.

Ultrafast multi-target control of tightly focused light fields

The control of ultrafast optical field is of great interest in developing ultrafast optics as well as the investigation on vari-ous light-matter interactions with ultrashort pulses.However,conventional spatial encoding approaches have only lim-ited steerable targets usually neglecting the temporal effect,thus hindering their broad applications.Here we present a new concept for realizing ultrafast modulation of multi-target focal fields based on the facile combination of time-depend-ent vectorial diffraction theory with fast Fourier transform.This is achieved by focusing femtosecond pulsed light carrying vectorial-vortex by a single objective lens under tight focusing condition.It is uncovered that the ultrafast temporal de-gree of freedom within a configurable temporal duration(~400 fs)plays a pivotal role in determining the rich and exotic features of the focused optical field at one time,namely,bright-dark alternation,periodic rotation,and longitudinal/trans-verse polarization conversion.The underlying control mechanisms have been unveiled.Besides being of academic in-terest in diverse ultrafast spectral regimes,these peculiar behaviors of the space-time evolutionary beams may underpin prolific ultrafast-related applications such as multifunctional integrated optical chip,high-efficiency laser trapping,micro-structure rotation,super-resolution optical microscopy,precise optical measurement,and liveness tracking.

Determination of volumetric elastic moduli of plant leaf cells based on pressure-volume curves

Volumetric elastic modulus （VEM） is an important parameter in biophysics and biomechanics of plants for in particular understanding cell growth. This paper proposes a new relation that can be used for precisely determining VEM. With the aid of this relation, it shows that the exponential approximation of the pressure-volume relationship adopted in most of the literatures in this field may lead to serious errors on VEM.

Is 2D stereological method good enough for quantification of solid oxide fuel cell electrode microstructure？

Nowadays,by the significant progresses in the development of solid oxide fuel cell(SOFC)materials and the thin-film fabrication methods for electrolyte,the performance of SOFC has been dominated by the microstructures of electrodes[1,2].Based on the first generation electrodes consisting of a single phase catalyst,the new generation electrodes consisting of interpenetrating percolating multiple phases with multiple functionalities have been usually employed in commercially-viable SOFCs[3].As

Scaling effects on combustion modes in a single-side expansion kerosene-fueled scramjet combustor

The combustion modes in two different scramjet combustors with the mass flow rates of 1.8 kg/s and 3.6 kg/s are experimentally investigated to explore the scaling effects on supersonic combustion with a Mach number 2.0 inflow.It is found that the scramjet combustor with a larger scale can broaden the flame rich blowout limit.As the Equivalence Ratio(ER)increases,the combustion in the small-scale combustor maintains in the cavity-stabilized mode,and the flamebase moves downstream along the cavity shear layer;however,the combustion in the large-scale combustor gradually transfers from the cavity-stabilized mode to the jet-wake-stabilized mode.The differences in the cavity residence time,the ignition delay time and the Damkohler number caused by different scales of the scramjet combustor are likely to account for the scaling effects on the combustion modes.

High-throughput 3D reconstruction of stochastic heterogeneous microstructures in energy storage materials

Stochastic heterogeneous microstructures are widely applied in structural and functional materials,playing a crucial role in determining their performance.X-ray tomography and focused ion beam serial sectioning are frequently used methods to reconstruct three-dimensional(3D)microstructures,yet are demanding techniques and are resolution-limited.Here,a highthroughput multi-stage 3D reconstruction method via distance correlation functions is developed using a single representatively large-sized 2D micrograph for stochastic microstructures,and verified by X-ray micro-tomography datasets of isotropic and anisotropic solid oxide fuel cell electrodes.This method provides an economic,easy-to-use and high-throughput approach for reconstructing stochastic heterogeneous microstructures for energy conversion and storage devices,and can readily be extended to other materials.

Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation

The use of solid oxide fuel cells(SOFCs)is a promising approach towards achieving sustainable electricity pro-duction from fuel.The utilisation of the hydrocarbons and biomass in SOFCs is particularly attractive owing to their wide distribution,high energy density,and low price.The long-term operation of SOFCs using such fuels remains difficult owing to a lack of an effective diagnosis and optimisation system,which requires not only a precise analysis but also a fast response.In this study,we developed a hybrid model for an on-line analysis of SOFCs at the cell level.The model combines a multi-physics simulation(MPS)and deep learning,overcoming the complexity of MPS for a model-based control system,and reducing the cost of building a database(compared with the experiments)for the training of a deep neural network.The maximum temperature gradient and heat generation are two target parameters for an efficient operation of SOFCs.The results show that a precise predic-tion can be achieved from a trained AI algorithm,in which the relative error between the MPS and AI models is less than 1%.Moreover,an online optimisation is realised using a genetic algorithm,achieving the maximum power density within the limitations of the temperature gradient and operating conditions.This method can also be applied to the prediction and optimisation of other non-liner,dynamic systems.