Strike Velocity Prediction of Stick Blunt Instruments Based on Backpropagation Neural Network

OBJECTIVES

To analyze and predict the striking velocity range of stick blunt instruments in different populations, and to provide basic data for the biomechanical analysis of blunt force injuries in forensic identification.

METHODS

Based on the Photron FASTCAM SA3 high-speed camera, Photron FASTCAM Viewer 4.0 and SPSS 26.0 software, the tester's maximum striking velocity of stick blunt instruments and related factors were calculated and analyzed, and inputed to the backpropagation (BP) neural network for training. The trained and verified BP neural network was used as the prediction model.

RESULTS

A total of 180 cases were tested and 470 pieces of data were measured. The maximum striking velocity range was 11.30-35.99 m/s. Among them, there were 122 female data, the maximum striking velocity range was 11.63-29.14 m/s; there were 348 male data, the maximum striking velocity range was 20.11-35.99 m/s. The maximum striking velocity of stick blunt instruments increased with the increase of weight and height, but there was no obvious increase trend in the male group; the maximum striking velocity decreased with age, but there was no obvious downward trend in the female group. The maximum striking velocity of stick blunt instruments has no significant correlation with the material and strike posture. The root mean square error (RMSE), the mean absolute error (MAE) and the coefficient of determination (R²) of the prediction results by using BP neural network were 2.16, 1.63 and 0.92, respectively.

CONCLUSIONS

The prediction model of BP neural network can meet the demand of predicting the maximum striking velocity of different populations.

Reconstruction and Quantitative Evaluation of Blunt Injury Cases by Finite Element Method

OBJECTIVES

To reconstruct the cases of acceleration craniocerebral injury caused by blunt in forensic cases by finite element method (FEM), and to study the biomechanical mechanism and quantitative evaluation method of blunt craniocerebral injury.

METHODS

Based on the established and validated finite element head model of Chinese people, the finite element model of common injury tool was established with reference to practical cases in the forensic identification, and the blunt craniocerebral injury cases were reconstructed by simulation software. The cases were evaluated quantitatively by analyzing the biomechanical parameters such as intracranial pressure, von Mises stress and the maximum principal strain of brain tissue.

RESULTS

In case 1, when the left temporal parietal was hit with a round wooden stick for the first time, the maximum intracranial pressure was 359 kPa; the maximum von Mises stress of brain tissue was 3.03 kPa at the left temporal parietal; the maximum principal strain of brain tissue was 0.016 at the left temporal parietal. When the right temporal was hit with a square wooden stick for the second time, the maximum intracranial pressure was 890 kPa; the maximum von Mises stress of brain tissue was 14.79 kPa at the bottom of right temporal lobe; the maximum principal strain of brain tissue was 0.103 at the bottom of the right temporal lobe. The linear fractures occurred at the right temporal parietal skull and the right middle cranial fossa. In case 2, when the forehead and left temporal parietal were hit with a round wooden stick, the maximum intracranial pressure was 370 kPa and 1 241 kPa respectively, the maximum von Mises stress of brain tissue was 3.66 kPa and 26.73 kPa respectively at the frontal lobe and left temporal parietal lobe, and the maximum principal strain of brain tissue was 0.021 and 0.116 respectively at the frontal lobe and left temporal parietal lobe. The linear fracture occurred at the left posterior skull of the coronary suture. The damage evaluation indicators of the simulation results of the two cases exceeded their damage threshold, and the predicted craniocerebral injury sites and fractures were basically consistent with the results of the autopsy.

CONCLUSIONS

The FEM can quantitatively evaluate the degree of blunt craniocerebral injury. The FEM combined with traditional method will become a powerful tool in forensic craniocerebral injury identification and will also become an effective means to realize the visualization of forensic evidence in court.

Effects of anodic titanium dioxide nanotubes of different diameters on macrophage secretion and expression of cytokines and chemokines

OBJECTIVES

To investigate effects of TiO2 nanotubes of different diameters on J744A.1 macrophage behaviour, secretion and expression of pro-inflammatory cytokines and chemokines.

MATERIALS AND METHODS

Macrophage-like J744A.1 cells were cultured on three types of Ti surface: mechanically polished titanium plus 30 and 80 nm TiO2 nanotube surfaces, for 4, 24 and 48 h. Macrophage adhesion and proliferation were assessed using CCK-8 assay. Levels of pro-inflammatory cytokines (TNF-α, IL-1β and IL-6) and chemokines (MCP-1 and MIP-1α) secreted into the supernatant were measured using the Cytometric Bead Arrays kit. TNF-α, MCP-1 and MIP-1α gene expression were quantitatively analysed by real-time PCR.

RESULTS

These show that TiO2 nanotube surfaces, especially of 80 nm TiO2 nanotube, benefited macrophage adhesion and proliferation, and reduced protein secretion and mRNA expression of TNF-α, MCP-1 and MIP-1α. IL-1β and IL-6 were undetectable on all the surfaces at all times.

CONCLUSIONS

TiO2 nanotube surfaces, especially of 80 nm TiO2 nanotube, reduced inflammatory response in vitro, which might be part of a basis for rapid osseointegration in implants with TiO2 nanotube surfaces in animal studies.