Detecting Traffic Information From Social Media Texts With Deep Learning Approaches

Mining traffic-relevant information from social media data has become an emerging topic due to the real-time and ubiquitous features of social media. In this paper, we focus on a specific problem in social media mining which is to extract traffic relevant microblogs from Sina Weibo, a Chinese microblogging platform. It is transformed into a machine learning problem of short text classification. First, we apply the continuous bag-of-word model to learn word embedding representations based on a data set of three billion microblogs. Compared to the traditional one-hot vector representation of words, word embedding can capture semantic similarity between words and has been proved effective in natural language processing tasks. Next, we propose using convolutional neural networks (CNNs), long short-term memory (LSTM) models and their combination LSTM-CNN to extract traffic relevant microblogs with the learned word embeddings as inputs. We compare the proposed methods with competitive approaches, including the support vector machine (SVM) model based on a bag of n-gram features, the SVM model based on word vector features, and the multi-layer perceptron model based on word vector features. Experiments show the effectiveness of the proposed deep learning approaches

Ukupna kinetika redukcije niskokvalitetnog piroluzita smjesom hemiceluloze i lignina kao redukcijskog sredstva

Manganese is widely used in many fields. Many efforts have been made to recover manganese from low-grade pyrolusite due to the depletion of high-grade manganese ore. Thus, it is of practical significance to develop a clean, energy-saving and environmentally friendly technical route to reduce the low-grade pyrolusite. The reported results show that biomass wastes from crops, crop waste, wood and wood waste are environmentally friendly, energy-saving, and low-cost reducing agents for roasting reduction of low-grade pyrolusite. Kinetics of the reduction reactions is necessary for an efficient design of biomass reduction of pyrolusite. Therefore, it is important to look for a general kinetics equation to describe the reduction of pyrolusite by different kinds of biomass, because there is a wide variety of biomass wastes, meaning that it is impossible to investigate the kinetics for each biomass waste. In this paper, thermal gravimetric analysis and differential thermal analysis were applied to study the overall reduction kinetics of pyrolusite using a mixture of hemicellulose and lignin, two major components of biomass. Overall reduction process is the overlap of the respective reduction processes. A new empirical equation based on the Johnson–Mehl–Avrami equation can be used to describe the respective reduction kinetics using hemicellulose and lignin as reductants, and the corresponding apparent activation energy is 30.14 kJ mol−1 and 38.91 kJ mol−1, respectively. The overall kinetic model for the reduction of pyrolusite by the mixture of hemicellulose and lignin can be simulated by the summation of the respective kinetics by considering their mass-loss fractions, while a unit step function was used to avoid the invalid conversion data. The obtained results in this work are necessary to understand the biomass reduction of pyrolusite and provide valuable assistance in the development of a general kinetics equation.Ukupna kinetika redukcije piroluzita istraživana je termogravimetrijom i diferencijalnom termogravimetrijom. Kao redukcijsko sredstvo upotrijebljeni su hemiceluloza i lignin, glavni sastojci poljoprivrednog biljnog biootpada, drva i drvnog otpada. Ukupnu redukciju čine isprepleteni pojedinačni redukcijski procesi. Kinetika redukcije piroluzita smjesom hemiceluloze i lignina može se opisati novom empirijskom jednadžbom temeljenoj na jednadžbi Johnson–Mehl–Avrami, a odgovarajuća prividna energija aktivacije iznosi 30.14 kJ mol−1, odnosno 38.91 kJ mol−1. Sveobuhvatna kinetika može se modelirati kao zbroj pojedinačnih udjela uzimajući u obzir masene udjele sastojaka smjese te uz primjenu jedinične odskočne funkcije kako bi se izbjegli nevaljani podaci

Cross-lingual part-of-speech tagging using word embedding

As one of semi-supervised learning approach, cross-lingual projection leverages existing resources from a resource-rich language when building tools for resource-poor languages. In this paper we attempt to make use of word embedding with anchor based label propagation to improve the accuracy of a cross-lingual projection task: cross-lingual part-of-speech tagging under the graph-based framework. Our approach uses bilingual parallel corpora and labeled data from the resource-rich side assuming that there is no labeled data or only a few labeled data in resource-poor language. The results suggest the efficacy of our approach over traditional label propagation with lexical feature for projecting part-of-speech information across languages, and show that a few of labeled data help to enhance the effect a lot in cross-lingual task

Reexamine the dark matter scenario accounting for the positron excess in a new cosmic ray propagation model

The positron excess in cosmic rays has stimulated a lot of interests in the last decade. The dark matter origin of the extra positrons has attracted great attention. However, the $\gamma$-ray search set very stringent constraints on the dark matter annihilation/decay rate, which leads to great disfavor of the dark matter scenario. In the work, we incorporate the recent progress in cosmic rays propagation and reexamine the dark matter scenario accounting for the positron excess. Recent observations indicate that cosmic rays propagation in the Milky Way may be not uniform and diffusion in the Galactic disk should be slower than that in the halo. In the spatial-dependent propagation model, the positrons/electrons are more concentrated in the disk and lead to smaller dark matter annihilation/decay rate to account for the positron excess and also a smaller deficit in the background positron flux. Especially for the $\mu^+\mu^-$ channel the positron spectrum fit the AMS-02 latest data perfectly and the annihilation rate satisfies all the present constraints from $\gamma$-ray and CMB observations.Comment: 11 pages, 4 figure

Radiation-induced brain structural and functional abnormalities in presymptomatic phase and outcome prediction: Radiation-Induced Brain Abnormalities

Radiation therapy, a major method of treatment for brain cancer, may cause severe brain injuries after many years. We used a rare and unique cohort of nasopharyngeal carcinoma patients with normal-appearing brains to study possible early irradiation injury in its presymptomatic phase before severe, irreversible necrosis happens. The aim is to detect any structural or functional imaging biomarker that is sensitive to early irradiation injury, and to understand the recovery and progression of irradiation injury that can shed light on outcome prediction for early clinical intervention. We found an acute increase in local brain activity that is followed by extensive reductions in such activity in the temporal lobe and significant loss of functional connectivity in a distributed, large-scale, high-level cognitive function-related brain network. Intriguingly, these radiosensitive functional alterations were found to be fully or partially recoverable. In contrast, progressive late disruptions to the integrity of the related far-end white matter structure began to be significant after one year. Importantly, early increased local brain functional activity was predictive of severe later temporal lobe necrosis. Based on these findings, we proposed a dynamic, multifactorial model for radiation injury and another preventive model for timely clinical intervention. Hum Brain Mapp 39:407-427, 2018. © 2017 Wiley Periodicals, Inc

Autophagy Is a Protective Response to the Oxidative Damage to Endplate Chondrocytes in Intervertebral Disc: Implications for the Treatment of Degenerative Lumbar Disc

Low back pain (LBP) is the leading cause of disability in the elderly. Intervertebral disc degeneration (IDD) was considered as the main cause for LBP. Degeneration of cartilaginous endplate was a crucial harmful factor during the initiation and development of IDD. Oxidative stress was implicated in IDD. However, the underlying molecular mechanism for the degeneration of cartilaginous endplate remains elusive. Herein, we found that oxidative stress could induce apoptosis and autophagy in endplate chondrocytes evidenced by western blot analysis, flow cytometry, immunofluorescence staining, GFP-LC3B transfection, and MDC staining. In addition, we also found that the apoptosis of endplate chondrocytes was significantly increased after the inhibition of autophagy by bafilomycin A1 shown by flow cytometry. Furthermore, mTOR pathway upstream autophagy was greatly suppressed suggested by western blot assay. In conclusion, our study strongly revealed that oxidative stress could increase autophagy and apoptosis of endplate chondrocytes in intervertebral disc. The increase of autophagy activity could prevent endplate chondrocytes from apoptosis. The autophagy in endplate chondrocytes induced by oxidative stress was mTOR dependent. These findings might shed some new lights on the mechanism for IDD and provide new strategies for the treatments of IDD

Effects of Ginkgo biloba Extract on Inflammatory Mediators (SOD, MDA, TNF-α, NF-κBp65, IL-6) in TNBS-Induced Colitis in Rats

Inflammatory mediators play a criticial role in ulcerative colitis immune and inflammatory processes. The aim of the study was to investigate the effects of Ginkgo biloba extract on inflammatory mediators (SOD, MDA, TNF-α, NF-κBp65, IL-6) in TNBS-induced colitis in rats. Colitis in rats was induced by colonic administration with 2,4,6-trinitrobenzene sulfonic acid (TNBS, 150 mg/kg). EGB in doses of (50, 100, 200 mg/kg) was administered for 4 weeks to protect colitis. The results showed that EGB could significantly ameliorate macroscopic and histological damage, evidently elevate the activities of SOD and reduce the contents of MDA, inhibit the protein and mRNA expressions of TNF-α, NF-κBp65, and IL-6 in the colon tissues of experimental colitis in a dose-dependent manner compared with the model group. We concluded that the probable mechanisms of EGB ameliorated inflammatory injury in TNBS-induced colitis in rats by its modulation of inflammatory mediators and antioxidatio

Optoelectronic properties and ultrafast carrier dynamics of copper iodide thin films

As a promising high mobility p-type wide bandgap semiconductor, copper iodide has received increasing attention in recent years. However, the defect physics/evolution are still controversial, and particularly the ultrafast carrier and exciton dynamics in copper iodide has rarely been investigated. Here, we study these fundamental properties for copper iodide thin films by a synergistic approach employing a combination of analytical techniques. Steady-state photoluminescence spectra reveal that the emission at ~420 nm arises from the recombination of electrons with neutral copper vacancies. The photogenerated carrier density dependent ultrafast physical processes are elucidated with using the femtosecond transient absorption spectroscopy. Both the effects of hot-phonon bottleneck and the Auger heating significantly slow down the cooling rate of hot-carriers in the case of high excitation density. The effect of defects on the carrier recombination and the two-photon induced ultrafast carrier dynamics are also investigated. These findings are crucial to the optoelectronic applications of copper iodide

Fast and accurate X-ray fluorescence computed tomography imaging with the ordered-subsets expectation maximization algorithm.

The ordered-subsets expectation maximization algorithm (OSEM) is introduced to X-ray fluorescence computed tomography (XFCT) and studied; here, simulations and experimental results are presented. The simulation results indicate that OSEM is more accurate than the filtered back-projection algorithm, and it can efficiently suppress the deterioration of image quality within a large range of angular sampling intervals. Experimental results of both an artificial phantom and cirrhotic liver show that with a satisfying image quality the angular sampling interval could be improved to save on the data-acquisition time when OSEM is employed. In addition, with an optimum number of subsets, the image reconstruction time of OSEM could be reduced to about half of the time required for one subset. Accordingly, it can be concluded that OSEM is a potential method for fast and accurate XFCT imaging