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| 1 | Incorporating travel time reliability in predicting the likelihood of severe crashes on arterial highways using non-parametric random-effect regression显示文摘Travel time reliability(TTR) modeling has gain attention among researchers’ due to its ability to represent road user satisfaction as well as providing a predictability of a trip travel time.Despite this significant effort,its impact on the severity of a crash is not well explored.This study analyzes the effect of TTR and other variables on the probability of the crash severity occurring on arterial roads.To address the unobserved heterogeneity problem,two random-effect regressions were applied;the Dirichlet random-effect(DRE)and the traditional random-effect(TRE) logistic regression.The difference between the two models is that the random-effect in the DRE is non-parametrically specified while in the TRE model is parametrically specified.The Markov Chain Monte Carlo simulations were adopted to infer the parameters’ posterior distributions of the two developed models.Using four-year police-reported crash data and travel speeds from Northeast Florida,the analysis of goodness-of-fit found the DRE model to best fit the data.Hence,it was used in studying the influence of TTR and other variables on crash severity.The DRE model findings suggest that TTR is statistically significant,at 95 percent credible intervals,influencing the severity level of a crash.A unit increases in TTR reduces the likelihood of a severe crash occurrence by 25 percent.Moreover,among the significant variables,alcohol/drug impairment was found to have the highest impact in influencing the occurrence of severe crashes.Other significant factors included traffic volume,weekends,speed,work-zone,land use,visibility,seatbelt usage,segment length,undivided/divided highway,and age. | Emmanuel Kidando Ren Moses Eren Erman Ozguven Thobias Sando | 2019 | Journal of Traffic and Transportation Engineering(English Edition)2019，6，5： | 4 |
| 2 | Assessment of traffic performance measures and safety based on driver age and experience:A microsimulation based analysis for an unsignalized T-intersection显示文摘Traffic safety and performance measures such as crash risk and queue lengths or travel times are influenced by several important factors including those related to environment,human,and roadway design,especially at intersections.Previous research has studied different aspects related to these factors,yet these characteristics are not fully investigated with a focus on age and experience of drivers.In this paper,we investigate this issue by using a two-phase approach via a case study application on a critical T-intersection in the City of Tallahassee,Florida.The first phase includes a scenario-based microsimulation analysis through the use of a microscopic simulation software,namely VISSIM,to illustrate the variations in traffic performance measures with respect to driver compositions of different age groups in the traffic stream.A variety of scenarios is created where the driving characteristics are provided as inputs to these scenarios in terms of decision making and risk taking.This is also supported by a sensitivity analysis conducted based on the driver composition in the traffic.The second phase includes the analysis of microsimulation outputs via a tool developed by Federal Highway Administration tool,namely the Surrogate Safety Assessment Model(SSAM),in order to determine the traffic conflicts that occur in each scenario.These conflicts are also compared with real-life crash data for validation purposes.Results show that(a) the differences in risk perception that affect driving behavior might be significant in influencing traffic safety and performance measures,and(b) the proposed approach is considerably successful in simulating the actual crash conflict points. | Mehmet Baran Ulak Eren Erman Ozguven Ren Moses Thobias Sando Walter Boot Yassir AbdelRazig John Olusegun Sobanjo | 2019 | Journal of Traffic and Transportation Engineering(English Edition)2019，6，5： | 2 |
| 3 | Infuence of intersection geometrics on the operation of triple left-turn lanes 显示文摘 | Thobias Sando Ren Moses | 2009 | Journal of Transportation Engineering2009，135，5： | 1 |
| 4 | Influence of Intersection Geometrics on the Operation of Triple Left-Turn Lanes显示文摘 | Thobias Sando Ren Moses | 2009 | Journal of transportation engineering2009，135，5： | 1 |
| 5 | Role of TGF-β1 and its Receptors in Breast Carcinogenesis:Evaluation of Gene Expression Patterns and Clinical Implications显示文摘OBJECTIVE Transforming growth factor β1 (TGF-β1) is a multifunc-tional cytokine that may play an important role in tumor development and progression. METHODS We evaluated gene expression patterns of TGF-β1 and its receptors [transforming growth factor β type I receptor (TβR-Ⅰ) and transforming growth factor β type II receptor (TβR-Ⅱ)] in tumor tissue from patients with breast cancer or with benign breast diseases (BBD) and adja-cent normal tissue from the patients with breast cancer. Included in the study were 527 breast cancer patients and 213 BBD patients who participated in the Shanghai Breast Cancer Study. RESULTS The expression levels of the TGF-β1, TβR-Ⅰand TβR-Ⅱ genes in breast tissue were quantified using real-time PCR. TβR-Ⅱ expres-sion in cancer tissue was decreased by over 50% as compared to either adjacent normal tissue from the same patients or benign tumor tissue from BBD patients (p<0.001). TGF-β1 expression was lower by approximately 20% in cancer tissue compared to adjacent normal tissue (p=0.14) or to be-nign tumor tissue (p=0.002). Although TβR-Ⅰ expression was also reduced in cancer tissue compared to adjacent normal tissue, or benign tumor tissue, the magnitude of the reduction was less apparent than that for TβR-Ⅱ. Compared to patients with the lowest tertile value for TβR-Ⅱ, patients with median tertile value for TβR-Ⅱ had more favorable overall survival (HR 0.47, 95% CI 0.27-0.85) and disease-free survival (HR 0.65, 95% CI 0.39-1.06). No apparent associations, however, were observed between TGF-β1 or TβR-Ⅰ expression and overall or disease-free survival. CONCLUSION The results from this study support the hypothesis that a decreased level of TβR-Ⅱ gene expression, and thus reduced TGF-β1 sensitivity, is related to breast tumor progression. | Wenjing Wang Aesun Shin Qiuyin Cai Zefang Ren Xiao-Ou Shu Yutang Gao Harold I. Moses Wei Lu Wei Zheng | 2007 | Chinese Journal of Clinical Oncology2007，4，3： | 1 |
| 6 | Accident and hazard prediction models for highway–rail grade crossings:a state-of-the-practice review for the USA显示文摘Highway–rail grade crossings(HRGCs)are one of the most dangerous segments of the transportation network.Every year numerous accidents are recorded at HRGCs between highway users and trains,between highway users and traffic control devices,and solely between highway users.These accidents cause fatalities,severe injuries,property damage,and release of hazardous materials.Researchers and state Departments of Transportation(DOTs)have addressed safety concerns at HRGCs in the USA by investigating the factors that may cause accidents at HRGCs and developed certain accident and hazard prediction models to forecast the occurrence of accidents and crossing vulnerability.The accident and hazard prediction models are used to identify the most hazardous HRGCs that require safety improvements.This study provides an extensive review of the state-of-the-practice to identify the existing accident and hazard prediction formulae that have been used over the years by different state DOTs.Furthermore,this study analyzes the common factors that have been considered in the existing accident and hazard prediction formulae.The reported performance and implementation challenges of the identified accident and hazard prediction formulae are discussed in this study as well.Based on the review results,the US DOT Accident Prediction Formula was found to be the most commonly used formula due to its accuracy in predicting the number of accidents at HRGCs.However,certain states still prefer customized models due to some practical considerations.Data availability and data accuracy were identified as some of the key model implementation challenges in many states across the country. | Olumide F.Abioye Maxim A.Dulebenets Junayed Pasha Masoud Kavoosi Ren Moses John Sobanjo Eren E.Ozguven | 2020 | Railway Engineering Science2020，28，3： | 0 |
| 7 | REGγ drives Lgr5^(+) stem cells to potentiate radiation induced intestinal regeneration显示文摘Leucine-rich repeat containing G protein-coupled receptor 5(Lgr5), a marker of intestinal stem cells(ISCs), is considered to play key roles in tissue homoeostasis and regeneration after acute radiation injury. However, the activation of Lgr5 by integrated signaling pathways upon radiation remains poorly understood. Here, we show that irradiation of mice with whole-body depletion or conditional ablation of REGγ in Lgr5^(+) stem cell impairs proliferation of intestinal crypts, delaying regeneration of intestine epithelial cells. Mechanistically, REGγ enhances transcriptional activation of Lgr5 via the potentiation of both Wnt and Hippo signal pathways. TEAD4 alone or cooperates with TCF4, a transcription factor mediating Wnt signaling, to enhance the expression of Lgr5. Silencing TEAD4 drastically attenuated β-catenin/TCF4 dependent expression of Lgr5. Together, our study reveals how REGγ controls Lgr5 expression and expansion of Lgr5+stem cells in the regeneration of intestinal epithelial cells.Thus, REGγ proteasome appears to be a potential therapeutic target for radiation-induced gastrointestinal disorders. | Xiangzhan Zhu Minglei Yang Zaijun Lin Solomon Kibreab Mael Ya Li Lili Zhang Yaqi Kong Yaodong Zhang Yuping Ren Jianhui Li Zimeng Wang Ying Zhang Bo yang Tingmei Huang Fangxia Guan Zhenlong Li Robb E Moses Lei Li Bing Wang Xiaotao Li Bianhong Zhang | 2022 | Science China(Life Sciences)2022，65，8： | 0 |
| 8 | An application of Bayesian multilevel model to evaluate variations in stochastic and dynamic transition of traffic conditions显示文摘This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes(DTTR).In the proposed analysis,hierarchical regression models fitted using Bayesian frameworks were used to calibrate the transition probabilities that describe the DTTR.Datasets of two sites on a freeway facility located in Jacksonville,Florida,were selected for the analysis.The traffic speed thresholds to define traffic regimes were estimated using the Gaussian mixture model(GMM).The GMM revealed that two and three regimes were adequate mixture components for estimating the traffic speed distributions for Site 1 and 2 datasets,respectively.The results of hierarchical regression models show that there is considerable evidence that there are heterogeneity characteristics in the DTTR associated with lateral lane locations.In particular,the hierarchical regressions reveal that the breakdown process is more affected by the variations compared to other evaluated transition processes with the estimated intra-class correlation(ICC)of about 73%.The transition from congestion on-set/dissolution(COD)to the congested regime is estimated with the highest ICC of 49.4%in the three-regime model,and the lowest ICC of 1%was observed on the transition from the congested to COD regime.On the other hand,different days of the week are not found to contribute to the variations(the highest ICC was 1.44%)on the DTTR.These findings can be used in developing effective congestion countermeasures,particularly in the application of intelligent transportation systems,such as dynamic lane-management strategies. | Emmanuel Kidando Ren Moses Thobias Sando Eren Erman Ozguven | 2019 | Journal of Modern Transportation2019，27，4： | 0 |
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