Traffic Crash Characteristics in Shenzhen, China from 2014 to 2016

Road traffic crashes cause fatalities and injuries of both drivers/passengers in vehicles and pedestrians outside, thus challenge public health especially in big cities in developing countries like China. Previous efforts mainly focus on a specific crash type or causation to examine the crash characteristics in China while lacking the characteristics of various crash types, factors, and the interplay between them. This study investigated the crash characteristics in Shenzhen, one of the biggest four cities in China, based on the police-reported crashes from 2014 to 2016. The descriptive characteristics were reported in detail with respect to each of the crash attributes. Based on the recorded crash locations, the land-use pattern was obtained as one of the attributes for each crash. Then, the relationship between the attributes in motor-vehicle-involved crashes was examined using the Bayesian network analysis. We revealed the distinct crash characteristics observed between the examined levels of each attribute, as well the interplay between the attributes. This study provides an insight into the crash characteristics in Shenzhen, which would help understand the driving behavior of Chinese drivers, identify the traffic safety problems, guide the research focuses on advanced driver assistance systems (ADASs) and traffic management countermeasures in China

4,6-Dibromo-2,3-dimethyl­phenol

The mol­ecule of the title compound, C8H8Br2O, is approximately planar with a maximum deviation of 0.063 (1) Å for one of the Br atoms. In the crystal, adjacent mol­ecules are joined inter­molecular O—H⋯O hydrogen bonds, forming chains parallel to [010]. The structure also features a short Br⋯Br inter­action of 3.362 (1) Å

Ectopic Fat Deposition on Insulin Sensitivity: Correlation of Hepatocellular Lipid Content and M Value

. Purpose. This study aimed to explore the relationship among insulin sensitivity and ectopic fat depots in participants with different glucose status. Methods. Fifty-nine men and women were enrolled in this study: 29 with normal glucose tolerance (NGT), 17 with impaired glucose tolerance (IGT), and 13 with type 2 diabetes mellitus (T2DM). All participants underwent a hyperinsulinemiceuglycemic clamp to assess the insulin sensitivity index ( value) and magnetic resonance imaging to measure the hepatocellular lipid content (HCL), skeletal muscle fat content including intramyocellular lipid (IMCL) and extramyocellular lipid (EMCL) of tibialis anterior (ta), and soleus muscle (sol). Results. The value of NGT group was higher than those of IGT and T2DM groups ( = 0.001). Participants with T2DM had the highest HCL and IMCL (ta) compared with those in NGT and IGT groups ( = 0.001). The value had an inverse relationship with HCL ( = −0.789, = 0.001), IMCL (sol) ( = −0.427, = 0.002), and IMCL (ta) ( = −0.419, = 0.002). Stepwise linear regression analysis showed that HCL (standardized = −0.416; = 0.001) had an independent relationship with value. Conclusions. Hepatocellular lipid content deposition happens earlier than skeletal muscle fat deposition. HCL is an independent risk factor for insulin resistance and may be used to evaluate the risk of developing T2DM as a noninvasive marker of insulin sensitivity index

Analysis of the Constituents in Rat Serum after Oral Administration of Fufang Zhenzhu Tiaozhi Capsule by UPLC–Q–TOF–MS/MS

A rapid and sensitive UPLC/Q–TOF–MS method has been established for analysis of the constituents in rat serum after oral administration of Fufang Zhenzhu Tiaozhi (FTZ) capsule, an effective compound prescription for treating hyperlipidemia in the clinic. The UPLC/MS information of samples was obtained first in FTZ preparation and FTZ-treated rat serum. Mass spectra were acquired in both negative and positive ion modes. Thirty-six constituents in rat serum after oral administration of FTZ were detected, including the alkaloids, ginsenosides, pentacyclic triterpenes, and their metabolites. These chemicals were identified based on the retention time and mass spectrometry data with those of authentic standards or comparison of the literatures reports. Twenty-seven prototype components originated from FTZ and nine were the metabolites of the FTZ constituents. These results shed light on the potential active constituents of the complex traditional Chinese medicinal formulas

Analysing the simultaneous effects of personalities, demographics, competition and collaboration : a case study with Indian politics

Twitter is widely regarded as a fast growing social networking medium. The massive amounts of data available on twitter encourage researchers to crawl and analyse data from it. The purpose of this project is to create a complete system which contains a twitter crawler, a multidimensional database, a data digester and an analytics engine. The crawler is used for the crawling of tweets, the multidimensional database for storing the crawled data and a data digester for formatting the data crawled before storing it into the database while the analytics engine used to perform analysis on the data. Due to the magnitude of this project, multiple students are allocated to it. The author of this report was involved in the schema design of the twitter database and came up with a list of the types of content of the tweets data to be crawled by the twitter crawler. The data digester and part-of-speech tagging for the analytics engine were developed by the author of this report as well. The testing of the system is spread over a period of 4 days, from 14th to 17th March 2014. Within these 4 days, a total of 8,021,933 tweets were collected. The objective of this project has been met as the data digester was found to have a large amount of data successfully. The collected tweets were also successfully formatted by the data digester and inserted into the database. The testing of the analytical engine shows that the Stanford POS tagger was able to identify the name of politician, political party or a state in India with a recall value of 1 and a precision value of 0.47. In order to crawl more relevant tweets relating to Indian politics, improvement should be made to how the twitter crawler crawls for tweets. Instead of keywords, the crawler should start crawling tweets from a list of twitter users which are very active in Indian politics. Currently the visualizer, operational database and twitter crawler reside on the same server. To improve performance of the overall system, two servers should be used; one for hosting the operational database and one for data warehousing.Bachelor of Engineering (Computer Engineering

Association between Crash Attributes and Drivers’ Crash Involvement: A Study Based on Police-Reported Crash Data

Understanding the association between crash attributes and drivers’ crash involvement in different types of crashes can help figure out the causation of crashes. The aim of this study was to examine the involvement in different types of crashes for drivers from different age groups, by using the police-reported crash data from 2014 to 2016 in Shenzhen, China. A synthetic minority oversampling technique (SMOTE) together with edited nearest neighbors (ENN) were used to solve the data imbalance problem caused by the lack of crash records of older drivers. Logistic regression was utilized to estimate the probability of a certain type of crashes, and odds ratios that were calculated based on the logistic regression results were used to quantify the association between crash attributes and drivers’ crash involvement in different types of crashes. Results showed that drivers’ involvement patterns in different crash types were affected by different factors, and the involvement patterns differed among the examined age groups. Knowledge generated from the present study could help improve the development of countermeasures for driving safety enhancement

3D Volumetric Modeling with Introspective Neural Networks

In this paper, we study the 3D volumetric modeling problem by adopting the Wasserstein introspective neural networks method (WINN) that was previously applied to 2D static images. We name our algorithm 3DWINN which enjoys the same properties as WINN in the 2D case: being simultaneously generative and discriminative. Compared to the existing 3D volumetric modeling approaches, 3DWINN demonstrates competitive results on several benchmarks in both the generation and the classification tasks. In addition to the standard inception score, the Frechet Inception Distance (FID) metric is´ also adopted to measure the quality of 3D volumetric generations. In addition, we study adversarial attacks for volumetric data and demonstrate the robustness of 3DWINN against adversarial examples while achieving appealing results in both classification and generation within a single model. 3DWINN is a general framework and it can be applied to the emerging tasks for 3D object and scene modeling.

Driver reliance characteristics on forward collision warning systems in adjacent vehicle cut-in situations

An evaluation method was investigated to assess driver reliance characteristics on forward collision warning systems based on a driving simulator to improve driving safety in adjacent vehicle cut-in situations. Using alarm timing (time to collision, TTC) as the control variable, driving behavior data from 12 participants were collected in adjacent vehicle cut-in situations. Two objective indexes (brake reliance index and secondary task index) and two subjective indexes (risk level index and trust level index) were proposed to establish the evaluation system model to realize the quantitative evaluation of driver reliance level on the systems. An L9(34) orthogonal experiment was designed and conducted. Regression models of driver reliance indexes were established. The results show that alarm timing is the most significant factor affecting driver reliance. A late alarm (TTC = 2.4 s) degrades the effectiveness of the systems, while an early alarm (TTC = 1.2 s) causes drivers’ over-reliance on the systems. Therefore, appropriately delaying the alarm timing (TTC = 1.8 s) can improve driver reliance for safety considerations

Ectopic Fat Deposition on Insulin Sensitivity: Correlation of Hepatocellular Lipid Content and M Value

Purpose. This study aimed to explore the relationship among insulin sensitivity and ectopic fat depots in participants with different glucose status. Methods. Fifty-nine men and women were enrolled in this study: 29 with normal glucose tolerance (NGT), 17 with impaired glucose tolerance (IGT), and 13 with type 2 diabetes mellitus (T2DM). All participants underwent a hyperinsulinemic-euglycemic clamp to assess the insulin sensitivity index (M value) and magnetic resonance imaging to measure the hepatocellular lipid content (HCL), skeletal muscle fat content including intramyocellular lipid (IMCL) and extramyocellular lipid (EMCL) of tibialis anterior (ta), and soleus muscle (sol). Results. The M value of NGT group was higher than those of IGT and T2DM groups (P=0.001). Participants with T2DM had the highest HCL and IMCL (ta) compared with those in NGT and IGT groups (P=0.001). The M value had an inverse relationship with HCL (r=-0.789, P=0.001), IMCL (sol) (r=-0.427, P=0.002), and IMCL (ta) (r=-0.419, P=0.002). Stepwise linear regression analysis showed that HCL (standardized β=-0.416; P=0.001) had an independent relationship with M value. Conclusions. Hepatocellular lipid content deposition happens earlier than skeletal muscle fat deposition. HCL is an independent risk factor for insulin resistance and may be used to evaluate the risk of developing T2DM as a noninvasive marker of insulin sensitivity index