Discriminative Topic Mining via Category-Name Guided Text Embedding

Mining a set of meaningful and distinctive topics automatically from massive text corpora has broad applications. Existing topic models, however, typically work in a purely unsupervised way, which often generate topics that do not fit users' particular needs and yield suboptimal performance on downstream tasks. We propose a new task, discriminative topic mining, which leverages a set of user-provided category names to mine discriminative topics from text corpora. This new task not only helps a user understand clearly and distinctively the topics he/she is most interested in, but also benefits directly keyword-driven classification tasks. We develop CatE, a novel category-name guided text embedding method for discriminative topic mining, which effectively leverages minimal user guidance to learn a discriminative embedding space and discover category representative terms in an iterative manner. We conduct a comprehensive set of experiments to show that CatE mines high-quality set of topics guided by category names only, and benefits a variety of downstream applications including weakly-supervised classification and lexical entailment direction identification.Comment: WWW 2020. (Code: https://github.com/yumeng5/CatE

Friction Surface Treatment Selection: Aggregate Properties, Surface Characteristics, Alternative Treatments, and Safety Effects

This study aimed to evaluate the long term performance of the selected surface friction treatments, including high friction surface treatment (HFST) using calcined bauxite and steel slag, and conventional friction surfacing, in particular pavement preservation treatments such as chip seal, microsurfacing, ultrathin bonded wearing course (UBWC), and diamond grinding. This study also attempted to determine the correlation between vehicle crash and pavement surface friction, which makes it possible to quantitatively establish the so-called crash modification factors (CMFs) that are extremely useful in selecting a cost-effective solution to reduce wet pavement vehicle crashes. In-depth reviews were conducted to identify the aspects of the properties for aggregates used in HFST, including aggregate abrasion value (AAV), Los Angeles abrasion (LAA), Micro-Deval abrasion, and polished stone value (PSV). Extensive laboratory testing was conducted to examine the LAA, Micro-Deval abrasion, and PSV, and to provide first-hand data on the calcined bauxite and steel slag that may be used for HFST and friction surfacing in Indiana. Laboratory accelerating polishing was carried out to evaluate the effect of aggregate gradation and identify the HFST systems with satisfactory friction performance with respect to surface macro-texture and friction. Test strips were installed in the pavement on a real-world road to further evaluate the friction performances of the promising HFST systems under the true traffic polishing and assess the potential effect of winter and snow plough. Pull-off testing was also conducted to examine the bonding between the proposed HFST systems and the substrate surface. Field friction test data was utilized to evaluate the long-term friction performances of pavement preservation treatments, including chip seal, microsurfacing, UBWC, and diamond grinding. Statewide vehicle crash data between 2010 and 2014 was examined to determine the crash statistics associated with pavement friction. The crash data was also matched to the annual pavement inventory friction data to quantify the probabilistic association between vehicle crash and pavement friction with respect to interstate, US, and state highways, respectively. Specification requirements were established for the properties of calcined bauxite and steel slag for HFST and friction surfacing with respect to LAA, Micro-Deval abrasion, PSV, Al2O3 content, and fine aggregate angularity (FAA). Specification requirements were also developed for HFST aggregate gradation and surface friction performance. Regression models were developed for predicting the friction numbers of chip seal, microsurfacing, UBWC, and diamond grinding over their service lives. Regression models were also provided to quantify the effectiveness of friction surfacing for interstate, US, and state highways, respectively

Usefulness of soluble endothelial protein C receptor combined with left ventricular global longitudinal strain for predicting slow coronary flow: A case-control study

Background: Slow coronary flow (SCF) is an angiographic entity characterized by delayed coronary opacification without an evident obstructive lesion in the epicardial coronary artery. However, patients with SCF have decreased left ventricular (LV) global longitudinal strain (GLS). SCF is associated with inflammation, and soluble endothelial protein C receptor (sEPCR) is a potential biomarker of inflammation. Therefore, under evaluation herein, was the relationship between SCF and sEPCR and the predictive value of sEPCR and LV GLS for SCF was investigated. Methods: Twenty-eight patients with SCF and 34 controls were enrolled. SCF was diagnosed by the thrombolysis in myocardial infarction frame count (TFC). The plasma level of sEPCR was quantified using enzyme-linked immunosorbent assay. LV GLS was measured by two-dimensional speckle-tracking echocardiography. Results: Plasma sEPCR was significantly higher in patients with SCF than in controls and was positively correlated with the mean TFC (r = 0.67, p < 0.001) and number of involved vessels (r = 0.61, p < 0.001). LV GLS was decreased in patients with SCF compared to that in controls. sEPCR level (OR = 3.14, 95% CI 1.55–6.36, p = 0.001) and LV GLS (OR = 1.44, 95% CI 1.02–2.04, p = 0.04) were independent predictors of SCF. sEPCR predicted SCF (area under curve [AUC]: 0.83); however, sEPCR > 9.63 ng/mL combined with LV GLS > −14.36% demonstrated better predictive power (AUC: 0.89; sensitivity: 75%; specificity: 91%). Conclusions: Patients with SCF have increased plasma sEPCR and decreased LV GLS. sEPCR may be a useful potential biomarker for SCF, and sEPCR combined with LV GLS can better predict SCF

Experimental and Numerical Analysis of Rock Burst Tendency and Crack Development Characteristics of Tianhu Granite

Rock burst is a serious nonlinear dynamic geological hazard in underground engineering construction. In this paper, a true triaxial unloading rock burst experiment and numerical simulation are carried out on Tianhu granite to investigate the rock burst tendency and crack development characteristics of surrounding rock after excavation. The experiment and numerical simulation process monitored the rock burst stress path to determine the rock burst stress. According to the evolution law of the frequency and amplitude of rock burst acoustic emission monitoring, the shape characteristics of rock burst fragments are analyzed. The rock burst numerical simulation analysis is carried out by the PFC software, and the temporal and spatial evolution law of cracks is obtained. The research results show that the laboratory experiment and numerical simulation of Tianhu granite have rock burst strengths of 163.4 MPa and 161 MPa, respectively, and the average rock burst stress ratio is 8.38, that is, the Tianhu granite has a low rock burst tendency. During the rock burst, the development of tensile cracks will produce flaky debris, and the development of shear cracks will produce lumpy debris. Rock burst will happen when the crack growth rate to be exceeded the unloading crack growth rate; therefore, it can be used as a precursor signal for the occurrence of rock burst

Development of active soft robotic manipulators for stable grasping under slippery conditions

Due to the requirements of industrial automation, soft manipulators are increasingly used in machinery manufacturing, metallurgy, and other fields. Typically, a manipulator is only suited to handle objects in ideal dry conditions, which limits the applications of these actuators. To solve the above-mentioned shortcomings in traditional grippers, this paper presents a friction-enhanced soft manipulator that has good flexibility and high interactivity and safety and is also equipped with a bionic nanofiber array film to provide stronger friction under slippery conditions. A polydimethylsiloxane (PDMS) nanofiber array film for increasing the friction of the soft manipulator was fabricated. A suitable manufacturing method for preparing the nanofiber array film was presented. The contact angle of the prepared nanofiber array film was measured. The experimental results showed that the soft robot manipulator performs extremely well under slippery conditions