The authors propose C&W-SP model — a text sentiment analysis model based on the representation learning. Firstly, an improved training model based on C&W model is proposed which can integrate emotional information and part of speech information in the training process of word embedding. The evaluation of data sets of NLP&CC’2013 is used to compare experimental results with different models. The experimental results show that the C&W-SP model which combines emotion information and part of speech information has the best performance and confirm the effectiveness of the proposed method.
Homogenization temperature of fluid inclusions, stratigraphic burial-thermal history, paeleostructure of accumulation period, known reservoirs and geochemical index are analyzed. Hydrocarbon accumulation periods, hydrocarbon transport system, trap-forming conditions of the Jurassic-Cretaceous in the hinterland of Junggar Basin are discussed. Thus, the dynamic accumulation process of the distant sourced, secondary-accumulated reservoirs is revealed. Results show that there are two periods of oil and gas charging in the Jurassic and cretaceous reservoirs in the hinterland of Junggar Basin, which are primary reservoirs formed in the early Cretaceous and secondary-filled reservoirs formed in the late paleogene till now. Both the primary reservoirs and sencondary accumulated reservoirs are widely spread in the hinterland area. Faults-sand bodies-unconformities act as three dimensional transporting systems for hydrocarbon migration and accumulation. The formation of primary reservoirs is controlled by paleostructure of accumulation period. During the later dissolution of paleostructure, primary reservoirs are destroyed and oil and gas migrate towards the north. Reservoirs types are decided by trap conditions on the migration pathways. At present, low-amplitude anticline, fault block and litho-stratigraphic reservoirs are the most discovered.
Analysis of exhaled VOCs from health and patients may help building association between VOCs and different diseases condition, which could offer a possibility of noninvasive monitoring of disease. VOCs were collected in 30 healthy subjects and 60 patients with upper respiratory tract infection. Analysis of 97 VOCs was performed by gas chromatography and mass spectrometry (GC-MS). The concentration of alkanes, alkenes, halogenated hydrocarbon, oxygenated hydrocarbons and aromatic hydrocarbons in health and patients breath was analyzed. Analysis of variance (ANOVA), principal component analysis (PCA) were used to analyze the VOC differences from patients and healthy ones. The results show that the concentration of isoprene differ among patients, healthy ones and indoor air (P<0.05). Patients show higher concentration of n-pentane compared to healthy ones (P<0.05). Patients with bacterial upper respiratory tract infection show higher concentration of propanal compared to healthy ones. The results of PCA show that there were significant VOC differences between patients with upper respiratory tract infection and healthy ones (P=0.019), but no differences between bacterial and non-bacterial upper respiratory tract infection.
By analyzing the characteristic of urban agglomeration areas, proposing that considering the mobility of resource is essential in researching carrying capacity, the research used core cities of Central Henan urban agglomeration as cases to study, referencing press-state-response model to build the target system of carrying capacity, considering resource supply and consumption & environmental pollution and treatment, using AHP method to evaluate. Reliant exponential is used to evaluate the dependence severity. The result shows that according to the comparison of two results considering resource fluidity or not in Zhengzhou in 2004?2014, only considering resource fluidity can reflect the real condition of an area. Core cities of Central Henan urban agglomeration are short of water and energy resources but are enough to use with the supply of external resources. The orders of the carrying capacity index on resource and environment are Luohe, Xuchang, Xinxiang, Zhengzhou, Jiyuan, Jiaozuo, Luoyang, Pingdingshan and Kaifeng. According to the reliant exponential of external resources, grain resources in these nine cities are self-sufficiency. External energy resources are needed in Kaifeng, Xinxiang, etc. External water resources are needed in Zhengzhou, Kaifeng, etc. More external water resources are needed than external water resources.
On the base of the 3D seismic profile interpretations, combined with the previous findings, geometry and tectonic evolution across and along the Laojunmiao break-thrust belt in the northern margin of the Northern Qilian belt are deciphered. The Laojunmiao belt is a bi-layer thrust system, consisting of a trishear faultpropagation fold system in the upper part, wedge-shaped thrust in the lower part. The Laojunmiao thrust system is linked with the NE-SW striking-slip 134 fault in the western segment, which forms a unified system of fracture on the Laojunmiao belt. Thrusting sheet above the hanging wall of the 134-Laojunmiao fault system is folded under nearly E-S compressive stress field, which results in the N-S striking folding to superpose on the Cenozoic bedding.
This paper presents an unsupervised method to identify internet new words from the large scale web corpus, which combines with an improved Point-wise Mutual Information (PMI), PMIk algorithm, and some basic rules. This method can recognize internet new words with length from 2 to n (n is any number as needed). Experimented based on 257 MB Baidu Tieba corpus, the precision of proposed system achieves 97.39% when the parameter value of PMIk algorithm is equal to 10, and the precision increases 28.79%, compared to PMI method. The results show that proposed system is significant and efficient for detecting new word from the large scale web corpus. Compiling the results of new word discovery into user dictionary and then loading the user dictionary into ICTCLAS (Institute of Computing Technology, Chinese Lexical Analysis System), experimented with 10 KB Baidu Tieba corpus, the precision, the recall and F-measure were promoted 7.93%, 3.73% and 5.91% respectively, compared with ICTCLAS. The result show that new word discovery could improve the performance of segmentation for web corpus significantly.
