A study on the application of diffuse axonal multi-axis general evaluation for braininjury assessment in small overlap barrier crash test

Purpose:Head injury criterion(HIC)companied by a rotation-based metric was widely believed to behelpful for head injury prediction in road traffic accidents.Recently,the Euro-New Car AssessmentProgram utilized a newly developed metric called diffuse axonal multi-axis general evaluation(DAMAGE)to explain test device for human occupant restraint(THOR)head injury,which demonstratedexcellent ability in capturing concussions and diffuse axonal injuries.However,there is still a lack ofcomprehensive understanding regarding the effectiveness of using DAMAGE for Hybrid III 50thpercentile male dummy(H50th)head injury assessment.The objective of this study is to determinewhether the DAMAGE could capture the risk of H50th brain injury during small overlap barrier tests.Methods:To achieve this objective,a total of 24 vehicle crash loading curves were collected as input datafor the multi-body simulation.Two commercially available mathematical dynamic models,namelyH50th and THOR,were utilized to investigate the differences in head injury response.Subsequently,adecision method known as simple additive weighting was employed to establish a comprehensive braininjury metric by incorporating the weighted HIC and either DAMAGE or brain injury criterion.Furthermore,35 sets of vehicle crash test data were used to analyze these brain injury metrics.Results:The rotational displacement of the THOR head is significantly greater than that of the H50thhead.The maximum linear and rotational head accelerations experienced by H50th and THOR modelswere(544.6±341.7)m/s^(2),(2468.2±1309.4)rad/s^(2) and(715.2±332.8)m/s^(2),(3778.7±1660.6)rad/s^(2),respectively.Under the same loading condition during small overlap barrier(SOB)tests,THOR exhibits ahigher risk of head injury compared to the H50th model.It was observed that the overall head injuryresponse during the small overlap left test condition is greater than that during the small overlap righttest.Additionally,an equation was formulated to establish the necessary relationship between theDAMAGE values of THOR and H50th.Conclusion:If H50th rather than THOR is employed as an evaluation tool in SOB crash tests,newlydesigned vehicles are more likely to achieve superior performance scores.According to the current injurycurve for DAMAGE and brain injury criterion,it is highly recommended that HIC along with DAMAGE wasprioritized for brain injury assessment in SOB tests.

Differences in cognitive profiles between traumatic brain injury and stroke： A comparison of the Montreal Cognitive Assessment and Mini-Mental State Examination

Purpose： To investigate the profiles of cognitive impairment through Montreal Cognitive Assessment （MoCA） and Mini-Mental State Examination （MMSE） in patients with chronic traumatic brain injury （TBI） or stroke and to evaluate the sensitivity of the two scales in patients with TBI. Methods： In this cohort study, a total of 230 patients were evaluated, including TBI group （n = 103） and stroke group （n - 127）. The cognitive functions of two groups were evaluated by designated specialists using MoCA （Beijing version） and MMSE （Chinese version）. Results： Compared with the patients with stroke, the patients with TBI received significantly lower score in orientation subtest and recall subtest in both tests. MoCA abnormal rates in the TBI group and stroke group were 94.17% and 86.61% respectively, while MMSE abnormal rates were 69.90% and 57.48%, respectively. In the TBI group, 87.10% patients with normal MMSE score had abnormal MoCA score and in the stroke group, about 70.37% patients with normal MMSE score had abnormal MoCA score. The diagnostic consistency of two scales in the TBI group and the stroke group were 72% and 69%, re.spectively. Conclusion： In our rehabilitation center, patients with TBI may have mare extensive and severe cognitive impairments than patients with stroke, prominently in orientation and recall domain. In screening post- TBI cognitive impairment, MoCA tends to be more sensitive than MIV[SE.

Image processing methods to evaluate tomato and zucchini damage in post-harvest stages

Through the supply chain,the quality or quality change of the products can generate important losses.The quality control in some steps is made manually that supposes a high level of subjectivity,controlling the quality and its evolution using automatic systems can suppose a reduction of the losses.Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study.Two steps in the supply chain are considered,the feeding of the raw products into the handling chain(because low quality generates a reduction of the chain productivity)and the cool storage of the processed products(as the value at the market is reduced).It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products(corresponding to specific farmers/suppliers,it should be asked to improve to maintain the productivity of the line).The second stage is analyzing the evolution of the products along the cool chain(storage and transport),the use of an App developed to be use under Android was proposed to substitute the“visual”evaluation used in practice.The algorithms used,including stages of pre-treatment,segmentation,analysis and presentation of the results take account of the short time available and the limited capacity of the batteries.High performance techniques were applied to the homography stage to discard some of the images,resulting in better performance.Also threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the products.The proposed method achieves success rates comparable to,and improving,the expert inspection.