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Continental tight oil sandstone reservoirs are developed in the Cretaceous Quentou Formation in the Songliao Basin, China. At present, there is still a lack of research on the reservoir microstructures, reservoir physical properties, and the division scheme of reservoir types in the Quan 3 Member of the Quanzhou Formation. Therefore, in this paper, taking the Quan 3 Member in the Fuxin Uplift Belt of the Songliao Basin as an example, the microscopic pore structure characteristics of tight oil sandstones have been systematically studied, and the classification standard of tight sandstones has been formulated. Furthermore, the sweet spots of the main production layers are predicted. The results show that the I sandstone group in the Quan 3 Member in the study area belongs to shallow water delta facies. Feldspar lithic fine sandstones are developed in the target layer, and calcareous sandstone is locally developed. Moreover, the mian pore types of the target layer include dissolved intergranular and intragranular pores, followed by primary intergranular pores, while micro-fractures are occasionally seen. According to the mercury intrusion test results, the pore-throat structures of the reservoir in the Quan 3 Member are divided into four types: 1) small-pore medium-throat type (point bar and delta distributary channel), 2) small-pore micro-throat type (point bar), 3) small-pore micro-throat type (natural levee), 4) micro-pore micro-throat type (river floodplain and inter-tributary bay). The lower limits of the physical properties of the effective reservoirs in the Quan 3 Member has been determined: the porosity is 10% and the permeability is 0.1 mD. Finally, combined with the study of the mercury intrusion curves, the physical properties and the sedimentary facies, the classification standard of the Quan 3 Member reservoirs was formulated. For the I sandstone group, the sweet spots of the Type I reservoirs are mainly developed in the Fuyu Oilfield in the southeast areas. The sandstones in this area suffered less compaction, and primary and secondary pores suffered from late dissolution are mainly developed.

Introduction There are increasing concerns about the negative impacts of chemotherapy near the end of life (EOL). There is discrepancy among different countries about its use, and little is known about the real-world situation in China. Patients and Methods This retrospective study was conducted at six representative hospitals across China. Adult decedents with a record of advanced solid cancer and palliative chemotherapy were consecutively screened from 2010 through 2014. The prevalence of EOL chemotherapy within the last 1 month of life was set as the primary outcome. The correlations among EOL chemotherapy, clinicopathological features, and overall survival (OS) were investigated. Results A total of 3,350 decedents who had had cancer were consecutively included; 2,098 (62.6%) were male and the median age was 56 years (range, 20–88). There were 177 (5.3%), 387 (11.6%), and 837 (25.0%) patients who received EOL chemotherapy within the last 2 weeks, 1 month, and 2 months of life, respectively. We identified inferior OS (median OS, 7.1 vs. 14.2 months; hazard ratio, 1.37; 95% confidence interval [CI], 1.23–1.53; p < .001), more intensive treatments (e.g., admitted to intensive care unit [ICU] in the last month of life, received cardiopulmonary resuscitation and invasive ventilation support), and hospital death (odds ratio, 1.53; 95% CI, 1.14–2.06; p = .005) among patients who received continued chemotherapy within the last month compared with those who did not. However, subgroup analyses indicated that receiving oral agents correlated with fewer ICU admissions and lower rates of in-hospital death. Conclusion This study showed that EOL chemotherapy is commonly used in China. Intravenous chemotherapy at the EOL significantly correlated with poor outcomes and the role of oral anticancer agents warrants further investigation.

We use a dynamic CGE model (SICGE) to assess the economic and climate impacts of emissions trading system (ETS) in China with a carbon price of 100 Yuan/ton CO2. A particular focus is given to the regulated electricity price regime, which is a major concern of electricity sector’s cost-effective participation in ETS in China. We found: (1) Carbon pricing is an effective policy for China to reduce CO2 emissions. Total CO2 emissions reduction ranges from 6.8% to 11.2% in short-term. (2) Rigid electricity price entails lower CO2 emissions reduction but can be considered as a feasible starting point to introduce carbon pricing policies in short-term as long as governmental subsidies are given to electricity production. (3) In mid- and long-term, the efficient policy is to earmark carbon revenue with competitive electricity price. We propose to use carbon revenue to reduce consumption tax in the first year of the introduction of carbon price and to use the carbon revenue to reduce production tax in following years.

For the problem of rolling bearing mechanical fault detection, this paper proposed a fault detection method based on wavelet packet energy spectrum and partial least squares (PLS). Firstly, the collected vibration signal was decomposed by wavelet packet into independent frequency bands. The different frequencies energy spectrum could be collected from the independent frequency bands. That means the energy spectrum feature vectors whose changes reflect the running state could be constructed. Then analyze the energy spectrum feature vector by PLS, and establish the fault detection model. The fault could be detected by the T2 and SPE statistics. Finally, the experimental results showed that the method is feasible and effective.

Considering the dual context of China's domestic willingness to have a cleaner export structure and the widespread concern among developed countries that carbon leakage from developing countries, particularly China, could threaten their own climate policy effectiveness; this paper uses the SICGE model to investigate the economic rationale of taxing direct CO 2 emissions of export in China. With an export carbon tax set at 200 yuan/t CO 2 , three policy scenarios were studied, where the tax revenue is: undistributed; redistributed neutrally to stimulate investment; and redistributed neutrally to stimulate consumption. According to the model, the economic and climate effects of the different policy scenarios are not particularly distinguishable. The economic impacts are slightly negative while the effect on the export structure is significant: the export of major energy-intensive products decreased and the export of certain sectors (labour-intensive or with higher value-added) increased, resulting in a cut of 3.77% in total direct CO 2 emissions from exports. The revenue redistribution to stimulate consumption is shown to be the optimal scenario choice, which was confirmed by further sensitivity tests. By reviewing related WTO laws, this paper concludes that a clearly designed export carbon tax with a comparable carbon price is in China's own interest, while lessening the carbon leakage concerns of developed countries.

In recent years, export value-added tax (VAT) refund rebate and export tax (EVRRET) measures have been adopted for energy-intensive products in China. They are proclaimed to be climate policy, yet there is no explicit and unique carbon cost set on export, and the implicit export carbon tax rates vary dramatically across sectors and over different periods. A method is provided to introduce an explicit and unique carbon cost into the current EVRRET. By setting a comparable carbon cost (US$20/tCO2 and US$30/tCO2) for eight major energy-intensive sectors to which the EVRRET is widely applied, it derives the corresponding ad valorem average rate for each sector. The introduction of a carbon cost into export VAT refund rebate policy would not increase the current export VAT refund rebate rate (except for the chemical sector), but would simply define a ceiling. However, the same introduction into the export tax policy would lead to an overall increase in sectoral export tax rates. In terms of competitiveness and...

Two furostanol saponins were obtained from the n-butanol fraction of methanol extract from Tupistra chinensis rhizomes, a folk medicine of Shennongjia Forest District of Hubei Province. Their structures were determinedas (25S)-26-O-(beta-D-glucopyranosyl)-furost-1 beta, 3 beta, 22 alpha, 26-tetrol-3-O-beta-D-glucopyranosyl-(1 -> 4)-beta-D-glucopyranosyl-(l -> 2)-beta-D-glucopyranoside (1) and (25R)26-O-(beta-D-glucopyranosyl)-furost-1 beta, 3 beta 22a, 26-tetrol 3-O-beta-D-glucopyranosyl-(l -> 4)-beta-D-glucopyranosyl-(l -> 2)-beta-D-glucopyranoside (2), on basis of chemical and spectroscopic evidences. 1 and 2 displayed marked inhibitory action towards COX-2 production in macrophages of the rat abdomen induced by LPS at 20 mu g/mL. (c) 2007 Kun Zou. Published by Elsevier B.V. on behalf of Chinese Chemical Society. All rights reserved.

The newly developed topological indices Am1–Am3 and the molecular connectivity indices mX were applied to multivariate analysis in structure–property correlation studies. The topological indices calculated from the chemical structures of some hydrocarbons were used to represent the molecular structures. The prediction of the retention indices of the hydrocarbons on three different kinds of stationary phase in gas chromatography can be achieved applying artificial neural networks and multiple linear regression models. The results from the artificial neural networks approach were compared with those of multiple linear regression models. It is shown that the predictive ability of artificial neural networks is superior to that of multiple linear regression method under the experimental conditions in this paper. Both the topological indices 2X and Am1 can improve the predicted results of the retention indices of the hydrocarbons on the stationary phase studied.

The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of background electrolytes (BGE) were applied as the input variables to ANN. The range of the performance voltage studied was from 15 to 27 kV, and that of the temperature in the capillary was from 20 to 30 ° C. For the pH values studied, the range was from 5.15 to 8.04. The range of the ionic strength investigated in this paper was from 0.040 to 0.097. The prediction abilities of ANN with different pre-processing procedure to the input variables were compared. Under the same performance conditions, the average prediction error of the migration time of the EOF marker was 5.46% with RSD = 1.76% according to 10 parallel runs of the optimized ANN structure by the proposed approach, and that of the 10 parallel predictions of the optimal ANN structure for the different performance conditions was 12.95% with RSD = 2.29% according to the proposed approach. The study showed that the proposed method could give better predicted results than other approaches discussed.

Background: Differentiating morphologic features based on hematoxylin-eosin (HE) staining is the most common method to classify pathological subtypes of non-small-cell lung cancer (NSCLC). However, its accuracy and inter-observer reproducibility in pathological diagnosis of poorly differentiated NSCLC remained to be improved. Materials and Methods: We attempted to explore the role of immunohistochemistry (IHC) staining in diagnosing pulmonary squamous cell carcinoma (SQCC) with poorly differentiated features by HE staining or with elevated serum adenocarcinoma-specific tumor markers (AD-TMs). We also compared the difference of epidermal growth factor receptor (EGFR) mutation rate between patients with confirmed SQCC and those with revised pathological subtype. Logistic regression analyses were used to test the association between different factors and diagnostic accuracy. Results: A total of 132 patients who met the eligible criteria and had adequate specimens for IHC confirmation were included. Pathological revised cases in poor differentiated subgroup, biopsy samples and high-level AD-TMs cases were more than those with high/moderate differentiation, surgical specimens and normal-level AD-TMs. Moreover, biopsy sample was a significant factor decreasing diagnostic accuracy of pathological subtype (OR, 4.037; 95% CI 1.446-11.267, p=0.008). Additionally, EGFR mutation rate was higher in patients with pathological diagnostic changes than those with confirmed SQCC (16.7% vs 4.4%, p=0.157). Conclusions: Diagnosis based on HE staining only might cause pathological misinterpretation in NSCLC patients with poor differentiation or high-level AD-TMs, especially those with biopsy samples. HE staining and IHC should be combined as pathological diagnostic standard. The occurrence of EGFR mutations in pulmonary SQCC might be overestimated.

Two clinical data sets were applied for pattern recognition in order to discover the correlation between urinary nucleoside profiles and tumours. One data set contains 168 clinical urinary samples, of which 84 specimens are from female thyroid cancer patients (malignant tumour group), and the other samples were collected from healthy women (normal group). However, 168 clinical urinary samples comprised the second data set, too. In all the specimens, each number of the samples for both uterine cervical cancer patients (malignant tumour group) and healthy females (normal group) is 60, and the other 48 samples were collected from uterine myoma patients (benign tumour group). For the two data sets, the separation and quantitative determination of the clinical urinary nucleosides were performed by capillary electrophoresis (CE). The pattern recognition was achieved applying multiple layer perceptron artificial neural networks (MLP ANN) based on conjugate gradient descent training algorithm. Moreover, applying the proposed principal component analysis (PCA) input selection scheme to MLP ANN, the accuracy rate of the pattern recognition was improved to some extent (or without any deterioration) even by much simpler structure of MLP ANN. The study showed that MLP ANN based on PCA input selection was a promising tool for pattern recognition.