Simulation and Analysis of the Buffer Function of Freeway Greening on Out-of-Control Vehicles

Freeway greening and traffic safety has aroused more and more attention. The purpose of this study is to investigate the role of flexible green planting in buffering out-of-control vehicles. The stopping distances of vehicle rushing into greening were tested at 8 group of initial speeds range from 5km/h to 40km/h in green belt, and a simplified mathematical model was built up to simulate the buffering process. The results indicated that the greening plants have certain buffering effect on vehicles and alleviate the crash damage within 30m of stopping distance for the vehicles under 40km/h, while the simplified mathematical model could reflect the buffering process of the plants actually by simulating the speed attenuation process, and it was found that the two types of resistance produced by the plants, i.e. counterforce of plants trunks and friction of branches and leaves, are the major factors during the vehicle deceleration.</p

EBF1, PAX5, and MYC: regulation on B cell development and association with hematologic neoplasms

During lymphocyte development, a diverse repertoire of lymphocyte antigen receptors is produced to battle against pathogens, which is the basis of adaptive immunity. The diversity of the lymphocyte antigen receptors arises primarily from recombination-activated gene (RAG) protein-mediated V(D)J rearrangement in early lymphocytes. Furthermore, transcription factors (TFs), such as early B cell factor 1 (EBF1), paired box gene 5 (PAX5), and proto-oncogene myelocytomatosis oncogene (MYC), play critical roles in regulating recombination and maintaining normal B cell development. Therefore, the aberrant expression of these TFs may lead to hematologic neoplasms

Promoting the process of determining brain death through standardized training

ObjectiveThis study aims to explore the training mode for brain death determination to ensure the quality of subsequent brain death determination.MethodsA four-skill and four-step (FFT) training model was adopted, which included a clinical neurological examination, an electroencephalogram (EEG) examination, a short-latency somatosensory evoked potential (SLSEP) examination, and a transcranial Doppler (TCD) examination. Each skill is divided into four steps: multimedia theory teaching, bedside demonstration, one-on-one real or dummy simulation training, and assessment. The authors analyzed the training results of 1,577 professional and technical personnel who participated in the FFT training model from 2013 to 2020 (25 sessions), including error rate analysis of the written examination, knowledge gap analysis, and influencing factors analysis.ResultsThe total error rates for all four written examination topics were &lt; 5%, at 4.13% for SLSEP, 4.11% for EEG, 3.71% for TCD, and 3.65% for clinical evaluation. The knowledge gap analysis of the four-skill test papers suggested that the trainees had different knowledge gaps. Based on the univariate analysis and the multiple linear regression analysis, among the six factors, specialty categories, professional and technical titles, and hospital level were the independent influencing factors of answer errors (p &lt; 0.01).ConclusionThe FFT model is suitable for brain death (BD) determination training in China; however, the authors should pay attention to the professional characteristics of participants, strengthen the knowledge gap training, and strive to narrow the difference in training quality

Genetic diversity and structure of the 4th cycle breeding population of Chinese fir (Cunninghamia lanceolata (lamb.) hook)

Studying population genetic structure and diversity is crucial for the marker-assisted selection and breeding of coniferous tree species. In this study, using RAD-seq technology, we developed 343,644 high-quality single nucleotide polymorphism (SNP) markers to resolve the genetic diversity and population genetic structure of 233 Chinese fir selected individuals from the 4th cycle breeding program, representing different breeding generations and provenances. The genetic diversity of the 4th cycle breeding population was high with nucleotide diversity (Pi) of 0.003, and Ho and He of 0.215 and 0.233, respectively, indicating that the breeding population has a broad genetic base. The genetic differentiation level between the different breeding generations and different provenances was low (Fst &lt; 0.05), with population structure analysis results dividing the 233 individuals into four subgroups. Each subgroup has a mixed branch with interpenetration and weak population structure, which might be related to breeding rather than provenance, with aggregation from the same source only being in the local branches. Our results provide a reference for further research on the marker-assisted selective breeding of Chinese fir and other coniferous trees

Experimental investigation of interfacial geometry associated with multiphase flow within a porous medium

Wood\u27s metal injection method is used to perform imbibitions and drainage of ethylene glycol into natural samples of Berea sandstone. Results on the measurement of interfacial area per volume (IAV) in this natural three-dimensional porous medium by the method of image analysis are presented. In Wood\u27s metal injection experiments, Wood\u27s metal was used to represent a non-wetting fluid and ethylene glycol (EG) was used to represent a wetting phase fluid. To determine the IAV for a Wood\u27s metal injected sample, images of the Wood\u27s-metal-injected core were taken with a Scanning Electron Microscope (SEM). This is the first attempt to perform IAV measurements within Berea sandstone based on a large quantity of SEM images. Measurements were performed on two-dimensional micro-models to quantify interfacial area per volume for known pore geometry as a function of fluid pressure and saturation. The transparent micro-models make it possible to visualize and quantify the fluid distributions within the samples and study the detailed capillary pressure-saturation-IAV relationship of each micro-model. The results have shown that as porosity increases, the hysteresis of IAV-saturation relationship decreases. The difference between the drainage and imbibition surfaces from the same sample is small. The theoretical capillary pressure values based on a theoretical equation cannot fit the measured values well and changes need to be made to this equation

Spatial-Temporal Analysis of Injury Severity with Geographically Weighted Panel Logistic Regression Model

This study is intended to investigate the influencing factors of injury severity by considering the heterogeneity issue of unobserved factors at different arterials and the spatial attributes in geographically weighted regression models. To achieve the objectives, geographically weighted panel logistic regression model was developed, in which the geographically weighted logistic regression model addressed the injury severity from the spatial perspective, while the panel data model accommodated the heterogeneity attributed to unobserved factors from the temporal perspective. The geo-crash data of Las Vegas metropolitan area from 2014 to 2016 was collected, involving 27 arterials with 25,029 injury samples. By comparing the conventional logistic regression model and geographically weighted logistic regression models, the geographically weighted panel logistic regression model showed preference to the other models. Results revealed that four main factors, human-beings (drivers/pedestrians/cyclists), vehicles, roadway, and environment, were potentially significant factors of increasing the injury severity. The findings provide useful insights for practitioners and policy makers to improve safety along arterials

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

This study intended to investigate the crash injury severity from the insights of the novice and experienced drivers. To achieve this objective, a bivariate panel data probit model was initially proposed to account for the correlation between both time-specific and individual-specific error terms. The geocrash data of Las Vegas metropolitan area from 2014 to 2017 were collected. In order to estimate two (seemingly unrelated) nonlinear processes and to control for interrelations between the unobservables, the bivariate random-effects probit model was built up, in which injury severity levels of novice and experienced drivers were addressed by bivariate (seemingly unrelated) probit simultaneously, and the interrelations between the unobservables (i.e., heterogeneity issue) were accommodated by bivariate random-effects model. Results revealed that crash types, vehicle types of minor responsibility, pedestrians, and motorcyclists were potentially significant factors of injury severity for novice drivers, while crash types, driver condition of minor responsibility, first harm, and highway factor were significant for experienced drivers. The findings provide useful insights for practitioners to improve traffic safety levels of novice and experienced drivers