A Hybrid Model for Sense Guessing of Chinese Unknown Words

PACLIC 23 / City University of Hong Kong / 3-5 December 200

SESS: A Self-Supervised and Syntax-Based Method for Sentiment Classification

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV

Saliency Driven Vasculature Segmentation with Infinite Perimeter Active Contour Model

Automated detection of retinal blood vessels plays an important role in advancing the understanding of the mechanism, diagnosis and treatment of cardiovascular disease and many systemic diseases, such as diabetic retinopathy and age-related macular degeneration. Here, we propose a new framework for precisely segmenting retinal vasculatures. The proposed framework consists of three steps. A non-local total variation model is adapted to the Retinex theory, which aims to address challenges presented by intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The image is then divided into superpixels, and a compactness-based saliency detection method is proposed to locate the object of interest. For better general segmentation performance, we then make use of a new infinite active contour model to segment the vessels in each superpixel. The proposed framework has wide applications, and the results show that our model outperforms its competitors

A distributed anomaly detection system for in-vehicle network using HTM

With the development of 5G and Internet of Vehicles technology, the possibility of remote wireless attack on an in-vehicle network has been proven by security researchers. Anomaly detection technology can effectively alleviate the security threat, as the first line of security defense. Based on this, this paper proposes a distributed anomaly detection system using hierarchical temporal memory (HTM) to enhance the security of a vehicular controller area network bus. The HTM model can predict the flow data in real time, which depends on the state of the previous learning. In addition, we improved the abnormal score mechanism to evaluate the prediction. We manually synthesized field modification and replay attack in data field. Compared with recurrent neural networks and hidden Markov model detection models, the results show that the distributed anomaly detection system based on HTM networks achieves better performance in the area under receiver operating characteristic curve score, precision, and recall

Experimental Verification of Solid-like and Fluid-like States in the Homogeneous Fluidization Regime of Geldart A Particles

The mechanisms underlying homogeneous fluidization of Geldart A particles have been debated for decades. Some ascribed the stability to interparticle forces, while others insisted a purely hydrodynamic explanation. Valverde et al. (2001) fluidized 8.53-μm (i.e., Geldart C) particles by the addition of fumed silica nanoparticles and found that even during homogeneous fluidization both solid-like and fluid-like behavior can be distinguished. However, it is still unclear whether both states exist for true Geldart A particles. In this paper, the particulate fluidization characteristics of three typical Geldart A powders were studied by camera recording, electrical capacitance tomography, and pressure fluctuation. For the first time, the existence of both a solid-like state dominated by interparticle forces and a fluid-like state dominated by fluid dynamics during homogeneous expansion of Geldart A particles was experimentally verified. Furthermore, the ability and performance of the used measurement techniques to identify different flow regimes were compared.</p

A novel 4-(1,3,4-thiadiazole-2-ylthio)pyrimidine derivative inhibits cell proliferation by suppressing the MEK/ERK signaling pathway in colorectal cancer

Colorectal cancer (CRC) is one of the most common types of malignant cancers worldwide. Although molecularly targeted therapies have significantly improved treatment outcomes, most of these target inhibitors are resistant. Novel inhibitors as potential anti-cancer drug candidates are still needed to be discovered. Therefore, in the present study, we synthesized a novel 4-(1,3,4-thiadiazole-2-ylthio)pyrimidine derivative (compound 4) using fragment- and structure-based techniques and then investigated the anti-cancer effect and underlying mechanism of anti-CRC. The results revealed that compound 4 significantly inhibited HCT116 cell proliferation with IC50 values of 8.04 ± 0.94 µmol L–1 after 48 h and 5.52 ± 0.42 µmol L–1 after 72 h, respectively. Compound 4 also inhibited colony formation, migration, and invasion of HCT116 cells in a dose-dependent manner, as well as inducing cell apoptosis and arresting the cell cycle in the G2/M phase. In addition, compound 4 was able to inhibit the activation of the MEK/ERK signaling in HCT116 cells. And compound 4 yielded the same effects as the MEK inhibitor U0126 on cell apoptosis and MEK/ERK-related proteins. These findings suggested that compound 4 inhibited cell proliferation and growth, and induced cell apoptosis, indicating its use as e a novel and potent anti-cancer agent against CRC via the MEK/ERK signaling pathway