Learn More
Bone cancer pain remains one of the most challenging cancer pains to fully control. In order to clarify bone cancer pain mechanisms and examine treatments, animal models mimicking the human condition are required. In our model of Walker 256 tumor cells implantation of the shaft of femur at the third trochanter level, the anatomical structure is relatively(More)
This paper aimed at evaluating the application of the genetic programming (GP) model for real-time crash prediction on freeways. Traffic, weather, and crash data used in this paper were obtained from the I-880N freeway in California, United States. The random forest (RF) technique was conducted to select the variables that affect crash risk under(More)
Human γδ T cells display the principal characteristics of professional antigen-presenting cells (APCs), in addition to playing a vital role in immunity through cytokine secretion and their cytotoxic activity. However, it is not clear whether γδ T cells perform APC-like functions under pathological conditions. In this study, we showed that, in contrast to(More)
BACKGROUND The human coagulation trigger tissue factor (TF) is overexpressed in several types of cancer and involved in tumor growth, vascularization, and metastasis. To explore the role of TF in biological processes of lung adenocarcinoma, we used RNA interference (RNAi) technology to silence TF in a lung adenocarcinoma cell line A549 with high-level(More)
The incidence of the autoimmune thyroid disease Hashimoto thyroiditis (HT) has increased in recent years, and increasing evidence supports the contribution of excess iodine intake to thyroid disease. In this study, we examined the status of autophagy and apoptosis in thyroid tissues obtained from patients with HT, and we determined the effects of excessive(More)
The study presented in this paper investigated the possibility of using support vector machine (SVM) models for crash injury severity analysis. Based on crash data collected at 326 freeway diverge areas, a SVM model was developed for predicting the injury severity associated with individual crashes. An ordered probit (OP) model was also developed using the(More)
The primary objective of this study is to divide freeway traffic flow into different states, and to evaluate the safety performance associated with each state. Using traffic flow data and crash data collected from a northbound segment of the I-880 freeway in the state of California, United States, K-means clustering analysis was conducted to classify(More)
Real-time crash risk prediction using traffic data collected from loop detector stations is useful in dynamic safety management systems aimed at improving traffic safety through application of proactive safety countermeasures. The major drawback of most of the existing studies is that they focus on the crash risk without consideration of crash severity.(More)
Studying drivers' route choice behavior under the influence of travel information is important because it provides insight to improve the effect of travel information on traffic environment. This paper mainly aims to study the impact of travel information on travelers' route choice behavior at different departure time. Multinomial logit model (MNL) is used(More)
Because of rampant security breaches in IoT devices, searching vulnerabilities in massive IoT ecosystems is more crucial than ever. Recent studies have demonstrated that control-flow graph (CFG) based bug search techniques can be effective and accurate in IoT devices across different architectures. However, these CFG-based bug search approaches are far from(More)