Radical-Enhanced Chinese Character Embedding

We present a method to leverage radical for learning Chinese character embedding. Radical is a semantic and phonetic component of Chinese character. It plays an important role as characters with the same radical usually have similar semantic meaning and grammatical usage. However, existing Chinese processing algorithms typically regard word or character as the basic unit but ignore the crucial radical information. In this paper, we fill this gap by leveraging radical for learning continuous representation of Chinese character. We develop a dedicated neural architecture to effectively learn character embedding and apply it on Chinese character similarity judgement and Chinese word segmentation. Experiment results show that our radical-enhanced method outperforms existing embedding learning algorithms on both tasks.Comment: 8 pages, 4 figure

Site-specific relapse pattern of the triple negative tumors in Chinese breast cancer patients

BACKGROUND: It has been reported that triple negative phenotype is characterized by aggressive clinical history in Western breast cancer patients, however its pattern of metastatic spread had never been reported in the Chinese population. Considering racial disparities, we sought to analyze the spread pattern for different sites of first recurrence in Chinese triple negative breast cancers. METHODS: A retrospective study of 1662 patients was carried out from a large database of breast cancer patients undergoing surgery between January 1, 2000 and March 31, 2004 at the Cancer Hospital, Fudan University, Shanghai, China. Survival curves were generated using the Kaplan-Meier method and annual relapse hazards were estimated by the hazard function. RESULTS: We found a statistically significant difference in relapse-free survival (RFS) for locoregional and visceral recurrence (P = 0.007 and P = 0.025, respectively) among the triple negative, ERBB2+ and HR+/ERBB2- subgroups in univariate analysis. In the multivariate Cox proportional hazards regression analysis, RFS for either locoregional or visceral relapse in the triple negative category was inferior to that in HR+/ERBB2- patients (P = 0.027 and P = 0.005, respectively), but comparable to that in ERBB2+ women (both P >0.05). Furthermore, the early relapse peak appeared later in the triple negative group than that in the ERBB2+ counterpart for both locoregional and visceral relapse. On the other hand, when compared with triple negative breast cancers, a significantly lower risk of developing bone relapse was discerned for ERBB2+ women (P = 0.048; HR = 0.384, 95% CI 0.148-0.991), with the borderline significance for HR+/ERBB2- breast cancers (P = 0.058; HR = 0.479, 95% CI 0.224-1.025). In terms of bone metastasis, the hazard rate remained higher for the triple negative category than that for the ERBB2+ subtype. CONCLUSION: Based on the site-specific spread pattern in different subgroups, the triple negative category of breast cancers in the Chinese population exhibits a different pattern of relapse, which indicates that different organotropism may be due to the different intrinsic subtypes. A better knowledge of the triple negative category is warranted for efficacious systemic regimens to decrease and/or delay the relapse hazard

Hyperchloremia Is Associated With Poorer Outcome in Critically Ill Stroke Patients

Background and Purpose: This study aims to explore the cause and predictive value of hyperchloremia in critically ill stroke patients.Materials and Methods: We conducted a retrospective study of a prospectively collected database of adult patients with first-ever acute ischemic stroke (AIS) or intracerebral hemorrhage (ICH) admitted to the neurointensive care unit (NICU) of a university-affiliated hospital, between January 2013 and December 2016. Patients were excluded if admitted beyond 72 h from onset, if they required neurocritical care for less than 72 h, and were treated with hypertonic saline within 72 h or had creatinine clearance less than 15 mL/min.Results: Of 405 eligible patients, the prevalence of hyperchloremia ([Cl−] ≥ 110 mmol/L) was 8.6% at NICU admission ([Cl−]0) and 17.0% within 72 h ([Cl−]max). Thirty-eight (9.4%) patients had new-onset hyperchloremia and 110 (27.1%) had moderate increase in chloride (Δ[Cl−] ≥ 5 mmol/L; Δ[Cl−] = [Cl−]max − [Cl−]0) in the first 72 h after admission, which were found to be determined by the sequential organ failure assessment score in multivariate logistic regression analysis. Neither total fluid input nor cumulative fluid balance had significant association with such chloride disturbance. New-onset hyperchloremia and every 5 mmol/L increment in Δ[Cl−] were both associated with increased odds of 30-day mortality and 6-month poor outcome, although no independent significance was found in multivariate models.Conclusion: Hyperchloremia tends to occur in patients more severely affected by AIS and ICH. Although no independent association was found, new-onset hyperchloremia and every 5 mmol/L increment in Δ[Cl−] were related to poorer outcome in critically ill AIS and ICH patients.Subject terms: clinical studies, intracranial hemorrhage, ischemic stroke, mortality/survival, quality and outcomes

Potential friendship discovery in social networks based on hybrid ensemble multiple collaborative filtering models in a 5G network environment

At present, 5G network technology is being applied to various social network modes, and it can provide technical and traffic support for social networks. Potential friendship discovery technology in 5G-enabled social networks is beneficial for users to make potential friends and expand their range of activities and social hierarchy, which is highly sought after in today's social networks and has great economic and application value. However, the sparsity of the dominant user association dataset in 5G-enabled social networks and the limitations of traditional collaborative filtering algorithms are two major challenges for the friend recommendation problem. Therefore, in order to overcome these problems regarding previous models, we propose a Hybrid Ensemble Multiple Collaborative Filtering Model (HEMCF) for discovering potential buddy relationships. The HEMCF model draws on a special autoencoder method that can effectively exploit the association matrix between friends and additional information to extract a hidden representation of users containing global structural information. Then, it uses the random walk-based graph embedding algorithm DeepWalk to extract another hidden representation of users in the buddy network containing local structural information. Finally, in the output module, the HEMCF model stacks and multiplies the two types of hidden representations of users to ensure that the information mentioned above is concentrated in the final output to generate the final prediction value. The magnitude of the prediction value represents the probability of the users being friends, with larger values representing a high probability of the two users being friends, and vice versa. Experimental results show that the proposed method boosts the accuracy of the relationship prediction over baselines on 3 real-world public datasets dramatically

Sensitivity Analysis of Rock Electrical Influencing Factors of Natural Gas Hydrate Reservoir in Permafrost Region of Qilian Mountain, China

It has been found that the relatively low abundance of gas hydrate in the Muli area of the Qilian Mountain causes gas hydrate reservoirs to have low-resistivity characteristics similar to those of low-resistivity oil and gas reservoirs. Therefore, it has great significance to research the main controlling factors affecting the electrical properties, and then come up a new logging identification and evaluation model for low-resistivity gas hydrate reservoirs. In this investigation, the rock samples of sandstone from gas hydrate reservoirs were scanned by CT and combined with gas hydrate distribution characteristics. The three-dimensional digital rocks with different hydrate saturation were constructed using the diffusion limited aggregation (DLA) model, and the resistivity was simulated via the finite element method. After sorting out the influencing factors of electrical characteristics, the sensitivity of the factors affecting electrical properties was evaluated using orthogonal analysis, using variance analysis and trend analysis to quantitatively evaluate the influencing factors of rock electrical sensitivity, so as to distinguish the main and secondary factors affecting rock electrical sensitivity. The results show that the sensitivity of rock electrical properties to the six influencing factors from strong to weak are: formation water salinity, water film thickness, shale content, conductive mineral content, micropores, and average coordination number

Performance Evaluation of Region-Based Convolutional Neural Networks Toward Improved Vehicle Taillight Detection

Increasingly serious traffic jams and traffic accidents pose threats to the social economy and human life. The lamp semantics of driving is a major way to transmit the driving behavior information between vehicles. The detection and recognition of the vehicle taillights can acquire and understand the taillight semantics, which is of great significance for realizing multi-vehicle behavior interaction and assists driving. It is a challenge to detect taillights and identify the taillight semantics on real traffic road during the day. The main research content of this paper is mainly to establish a neural network to detect vehicles and to complete recognition of the taillights of the preceding vehicle based on image processing. First, the outlines of the preceding vehicles are detected and extracted by using convolutional neural networks. Then, the taillight area in the Hue-Saturation-Value (HSV) color space are extracted and the taillight pairs are detected by correlations of histograms, color and positions. Then the taillight states are identified based on the histogram feature parameters of the taillight image. The detected taillight state of the preceding vehicle is prompted to the driver to reduce traffic accidents caused by the untimely judgement of the driving intention of the preceding vehicle. The experimental results show that this method can accurately identify taillight status during the daytime and can effectively reduce the occurrence of confused judgement caused by light interference

Predictors of extubation failure in neurocritical patients identified by a systematic review and meta-analysis.

BACKGROUND: Prediction of extubation failure, particularly in neurocritical patients, is unique and controversial. We conducted a systematic review and meta-analysis to identify the risk factors for extubation failure in these patients. METHODS: A literature search of databases (MEDLINE, EMBASE, the Cochrane Library, and Web of Science) was performed up to August of 2013 to identify trials that evaluated extubation failure predictors. Included trials were either prospective or retrospective cohort studies. RESULTS: Nine studies involving 928 participants were included. The systematic review and meta-analysis revealed that the following were predictive for extubation failure: pneumonia, atelectasis, mechanical ventilation of >24 h, a low Glasgow Coma Scale score (7-9T) (OR = 4.96, 95% CI = 1.61-15.26, P = 0.005), the inability to follow commands (OR = 2.07, 95% CI = 1.15-3.71, P = 0.02), especially the command to close the eyes, thick secretion, and no intact gag reflex. Meanwhile, the following were not predictive for extubation failure: sex, secretion volume, coughing upon suctioning, and the inability to follow one command among showing two fingers, wiggling the toes, or coughing on command. Additionally, some traditional weaning parameters were shown to poorly predict extubation failure in neurocritical patients. CONCLUSIONS: Besides pneumonia, atelectasis, and the duration of mechanical ventilation, other factors that should be taken into consideration in the prediction of extubation failure when neurocritical patients are weaned from tracheal intubation include neurologic abilities (Glasgow Coma Scale score and following commands), the secretion texture, and the presence of a gag reflex