Spatial Analysis of the Impact of Street-level Built Environment and Perception Features on the Crashes by Severity

Liu Yiping,Chen Tiantian,Chung Hyungchul,Jang Kitae 대한교통학회 2024 대한교통학회 학술대회지 Vol.90 No.-

Urban traffic accidents are closely related to street characteristics, and investigating this relationship is crucial for enhancing traffic safety. Street-level features primarily include the built environment elements that makes up the streets, such as greenery, sky, and other elements. As users of urban street spaces, travelers perception indicators of various streets also include subjective perspectives describing the differential characteristics among urban streets. Therefore, this study focuses on exploring the impact of the street built-environment and travelers perception indicators on the crash frequencies. The modeling process considers severity levels related to traffic crashes and then extends analysis to geospatial dimension to account for the spatial heterogeneity and correlation of coefficients. The study uses 587 road segments in the central area of Daejeon in Korea, with traffic crash data from the full year of 2019. All crashes are classified into killed/severe injury (KSI) and slight injury. Street built-environment elements are extracted from the street view images of the studied road sections using semantic segmentation technology, while street perception indicators are scored using deep learning methods based on the street view images, outputting results in six perceptual dimensions to create related variables. In addition, the impact of traffic variables such as AADT and road geometry (number of lanes, speed limits, etc.) is considered. The results suggest significant correlations among street built-environment, travelers perception indicators and the frequency of traffic crashes, with different trends of impact for various crash classification. The estimation results of coefficients also show variations in the spatial influence of different feature, which could help traffic authorities identify high-risk areas and understand contributing factors, thereby taking precaution actions.

Localized reliability analysis on a large-span rigid frame bridge based on monitored strains from the long-term SHM system

Liu, Zejia,Li, Yinghua,Tang, Liqun,Liu, Yiping,Jiang, Zhenyu,Fang, Daining Techno-Press 2014 Smart Structures and Systems, An International Jou Vol.14 No.2

With more and more built long-term structural health monitoring (SHM) systems, it has been considered to apply monitored data to learn the reliability of bridges. In this paper, based on a long-term SHM system, especially in which the sensors were embedded from the beginning of the construction of the bridge, a method to calculate the localized reliability around an embedded sensor is recommended and implemented. In the reliability analysis, the probability distribution of loading can be the statistics of stress transferred from the monitored strain which covered the effects of both the live and dead loads directly, and it means that the mean value and deviation of loads are fully derived from the monitored data. The probability distribution of resistance may be the statistics of strength of the material of the bridge accordingly. With five years' monitored strains, the localized reliabilities around the monitoring sensors of a bridge were computed by the method. Further, the monitored stresses are classified into two time segments in one year period to count the loading probability distribution according to the local climate conditions, which helps us to learn the reliability in different time segments and their evolvement trends. The results show that reliabilities and their evolvement trends in different parts of the bridge are different though they are all reliable yet. The method recommended in this paper is feasible to learn the localized reliabilities revealed from monitored data of a long-term SHM system of bridges, which would help bridge engineers and managers to decide a bridge inspection or maintenance strategy.

Localized reliability analysis on a large-span rigid frame bridge based on monitored strains from the long-term SHM system

Zejia Liu,Liqun Tang,Yinghua Li,Yiping Liu,Zhenyu Jiang,Daining Fang 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.14 No.2

With more and more built long-term structural health monitoring (SHM) systems, it has been considered to apply monitored data to learn the reliability of bridges. In this paper, based on a long-term SHM system, especially in which the sensors were embedded from the beginning of the construction of the bridge, a method to calculate the localized reliability around an embedded sensor is recommended and implemented. In the reliability analysis, the probability distribution of loading can be the statistics of stress transferred from the monitored strain which covered the effects of both the live and dead loads directly, and it means that the mean value and deviation of loads are fully derived from the monitored data. The probability distribution of resistance may be the statistics of strength of the material of the bridge accordingly. With five years\' monitored strains, the localized reliabilities around the monitoring sensors of a bridge were computed by the method. Further, the monitored stresses are classified into two time segments in one year period to count the loading probability distribution according to the local climate conditions, which helps us to learn the reliability in different time segments and their evolvement trends. The results show that reliabilities and their evolvement trends in different parts of the bridge are different though they are all reliable yet. The method recommended in this paper is feasible to learn the localized reliabilities revealed from monitored data of a long-term SHM system of bridges, which would help bridge engineers and managers to decide a bridge inspection or maintenance strategy

Regularization statistical inferences for partially linear models with high dimensional endogenous covariates

Liu Changqing,Zhao Peixin,Yang Yiping 한국통계학회 2021 Journal of the Korean Statistical Society Vol.50 No.1

In this paper, we consider the statistical inferences for a class of partially linear models with high dimensional endogenous covariates, when high dimensional instrumental variables are also available. A regularized estimation procedure is proposed for identifying the optimal instrumental variables, and estimating covariate efects of the parametric and nonparametric components. Under some conditions, some theoretical properties are studied, such as the consistency of the optimal instrumental variable identifcation and signifcant covariate selection. Furthermore, some simulation studies and a real data analysis are carried out to examine the fnite sample performance of the proposed method.

Mussel-Inspired Multifunctional Coating for Enhancing the UV-Resistant Property of Polypropylene Fibers

Zhengyi Liu,Juncheng Hu,Qi Sun,Li Chen,Xia Feng,Yiping Zhao 한국고분자학회 2017 Macromolecular Research Vol.25 No.5

In this paper, UV-resistant polypropylene (PP) fibers were prepared with a simple and versatile strategy. The PP fiber was firstly coated a polydopamine (PDA) layer by simply dipping the fiber into an alkaline dopamine solution. Then, the titania (TiO2) nanoparticles were chemically bound to the PDA layer through the reduction capacity of catechol groups in PDA, endowing the fibers with excellent UVresistant properties. The surface chemical composition of modified fibers was confirmed by attenuated total reflectance fourier transform infrared (ATR-FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). The surface morphology and the crystalline structure of the modified fibers were studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD) respectively. Thermo stability was characterized by thermogravimetry analysis. Besides, the mechanical and UV protection properties were further investigated through monofilament tensile and the UV transmittance test. The results showed that the PDA and TiO2 were successfully coated on fiber surface. Comprared to the pristine fiber, the modified fiber exhibited better thermal stability. Particularly, the as-prepared PP-PDA-TiO2 fibers could strongly resist the UV rays with no change in mechanical properties.

Forensic biogeographical ancestry inference: recent insights and current trends

Wen Yufeng,Liu Jing,Su Yonglin,Chen Xiacan,Hou Yiping,Liao Linchuan,Wang Zheng 한국유전학회 2023 Genes & Genomics Vol.45 No.10

Background As a powerful complement to the paradigmatic DNA profiling strategy, biogeographical ancestry inference (BGAI) plays a significant part in human forensic investigation especially when a database hit or eyewitness testimony are not available. It indicates one’s biogeographical profile based on known population-specific genetic variations, and thus is crucial for guiding authority investigations to find unknown individuals. Forensic biogeographical ancestry testing exploits much of the recent advances in the understanding of human genomic variation and improving of molecular biology. Objective In this review, recent development of prospective ancestry informative markers (AIMs) and the statistical approaches of inferring biogeographic ancestry from AIMs are elucidated and discussed. Methods We highlight the research progress of three potential AIMs (i.e., single nucleotide polymorphisms, microhaplotypes, and Y or mtDNA uniparental markers) and discuss the prospects and challenges of two methods that are commonly used in BGAI. Conclusion While BGAI for forensic purposes has been thriving in recent years, important challenges, such as ethics and responsibilities, data completeness, and ununified standards for evaluation, remain for the use of biogeographical ancestry information in human forensic investigations. To address these issues and fully realize the value of BGAI in forensic investigation, efforts should be made not only by labs/institutions around the world independently, but also by inter-lab/institution collaborations.

A New Insight into the Role of Calpains in Post-mortem Meat Tenderization in Domestic Animals: A review

Lian, Ting,Wang, Linjie,Liu, Yiping Asian Australasian Association of Animal Productio 2013 Animal Bioscience Vol.26 No.3

Tenderness is the most important meat quality trait, which is determined by intracellular environment and extracellular matrix. Particularly, specific protein degradation and protein modification can disrupt the architecture and integrity of muscle cells so that improves the meat tenderness. Endogenous proteolytic systems are responsible for modifying proteinases as well as the meat tenderization. Abundant evidence has testified that calpains (CAPNs) including calpain I (CAPN1) and calpastatin (CAST) have the closest relationship with tenderness in livestock. They are involved in a wide range of physiological processes including muscle growth and differentiation, pathological conditions and post-mortem meat aging. Whereas, Calpain3 (CAPN3) has been established as an important activating enzyme specifically expressed in livestock's skeletal muscle, but its role in domestic animals meat tenderization remains controversial. In this review, we summarize the role of CAPN1, calpain II (CAPN2) and CAST in post-mortem meat tenderization, and analyse the relationship between CAPN3 and tenderness in domestic animals. Besides, the possible mechanism affecting post-mortem meat aging and improving meat tenderization, and current possible causes responsible for divergence (whether CAPN3 contributes to animal meat tenderization or not) are inferred. Only the possible mechanism of CAPN3 in meat tenderization has been confirmed, while its exact role still needs to be studied further.

Statistics and probability analysis of vehicle overloads on a rigid frame bridge from long-term monitored strains

Li, Yinghua,Tang, Liqun,Liu, Zejia,Liu, Yiping Techno-Press 2012 Smart Structures and Systems, An International Jou Vol.9 No.3

It is well known that overloaded vehicles may cause severe damages to bridges, and how to estimate and evaluate the status of the overloaded vehicles passing through bridges become a challenging problem. Therefore, based on the monitored strain data from a structural health monitoring system (SHM) installed on a bridge, a method is recommended to identify and analyze the probability of overloaded vehicles. Overloaded vehicle loads can cause abnormity in the monitored strains, though the abnormal strains may be small in a concrete continuous rigid frame bridge. Firstly, the abnormal strains are identified from the abundant strains in time sequence by taking the advantage of wavelet transform in abnormal signal identification; secondly, the abnormal strains induced by heavy vehicles are picked up by the comparison between the identified abnormal strains and the strain threshold gotten by finite element analysis of the normal heavy vehicle; finally, according to the determined abnormal strains induced by overloaded vehicles, the statistics of the overloaded vehicles passing through the bridge are summarized and the whole probability of the overloaded vehicles is analyzed. The research shows the feasibility of using the monitored strains from a long-term SHM to identify the information of overloaded vehicles passing through a bridge, which can help the traffic department to master the heavy truck information and do the damage analysis of bridges further.

Polymorphisms in the Perilipin Gene May Affect Carcass Traits of Chinese Meat-type Chickens

Lu Zhang,Qing Zhu,Yiping Liu,Elizabeth R. Gilbert,Diyan Li,Huadong Yin,Yan Wang,Zhiqin Yang,Zhen Wang,Yuncong Yuan,Xiao-Ling Zhao 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.6

Improved meat quality and greater muscle yield are highly sought after in high-quality chicken breeding programs. Past studies indicated that polymorphisms of the Perilipin gene (PLIN1) are highly associated with adiposity in mammals and are potential molecular markers for improving meat quality and carcass traits in chickens. In the present study, we screened single nucleotide polymorphisms (SNPs) in all exons of the PLIN1 gene with a direct sequencing method in six populations with different genetic backgrounds (total 240 individuals). We evaluated the association between the polymorphisms and carcass and meat quality traits. We identified three SNPs, located on the 5′ flanking region and exon 1 of PLIN1 on chromosome 10 (rs315831750, rs313726543, and rs80724063, respectively). Eight main haplotypes were constructed based on these SNPs. We calculated the allelic and genotypic frequencies, and genetic diversity parameters of the three SNPs. The polymorphism information content (PIC) ranged from 0.2768 to 0.3750, which reflected an intermediate genetic diversity for all chickens. The CC, CT, and TT genotypes influenced the percentage of breast muscle (PBM), percentage of leg muscle (PLM) and percentage of abdominal fat at rs315831750 (p<0.05). Diplotypes (haplotype pairs) affected the percentage of eviscerated weight (PEW) and PBM (p<0.05). Compared with chickens carrying other diplotypes, H3H7 had the greatest PEW and H2H2 had the greatest PBM, and those with diplotype H7H7 had the smallest PEW and PBM. We conclude that PLIN1 gene polymorphisms may affect broiler carcass and breast muscle yields, and diplotypes H3H7 and H2H2 could be positive molecular markers to enhance PEW and PBM in chickens.

Polymorphisms in the Perilipin Gene May Affect Carcass Traits of Chinese Meat-type Chickens

Zhang, Lu,Zhu, Qing,Liu, Yiping,Gilbert, Elizabeth R.,Li, Diyan,Yin, Huadong,Wang, Yan,Yang, Zhiqin,Wang, Zhen,Yuan, Yuncong,Zhao, Xiaoling Asian Australasian Association of Animal Productio 2015 Animal Bioscience Vol.28 No.6

Improved meat quality and greater muscle yield are highly sought after in high-quality chicken breeding programs. Past studies indicated that polymorphisms of the Perilipin gene (PLIN1) are highly associated with adiposity in mammals and are potential molecular markers for improving meat quality and carcass traits in chickens. In the present study, we screened single nucleotide polymorphisms (SNPs) in all exons of the PLIN1 gene with a direct sequencing method in six populations with different genetic backgrounds (total 240 individuals). We evaluated the association between the polymorphisms and carcass and meat quality traits. We identified three SNPs, located on the 5' flanking region and exon 1 of PLIN1 on chromosome 10 (rs315831750, rs313726543, and rs80724063, respectively). Eight main haplotypes were constructed based on these SNPs. We calculated the allelic and genotypic frequencies, and genetic diversity parameters of the three SNPs. The polymorphism information content (PIC) ranged from 0.2768 to 0.3750, which reflected an intermediate genetic diversity for all chickens. The CC, CT, and TT genotypes influenced the percentage of breast muscle (PBM), percentage of leg muscle (PLM) and percentage of abdominal fat at rs315831750 (p<0.05). Diplotypes (haplotype pairs) affected the percentage of eviscerated weight (PEW) and PBM (p<0.05). Compared with chickens carrying other diplotypes, H3H7 had the greatest PEW and H2H2 had the greatest PBM, and those with diplotype H7H7 had the smallest PEW and PBM. We conclude that PLIN1 gene polymorphisms may affect broiler carcass and breast muscle yields, and diplotypes H3H7 and H2H2 could be positive molecular markers to enhance PEW and PBM in chickens.