Sichuan University

About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.

Possibility Distribution-Based Approach for MAGDM With Hesitant Fuzzy Linguistic Information

Abstract: In group decision making (GDM) with qualitative settings, experts may require several possible linguistic values rather than a single term to express their preferences. A hesitant fuzzy linguistic term set has recently been developed to manage this situation. In line with this development, in this paper, we present a new framework model to address multiple attribute GDM with hesitant fuzzy linguistic information. First, the concept of a possibility distribution is defined. Based on the possibility distributions, some aggregation operators such as the hesitant fuzzy linguistic weighted average operator and the hesitant fuzzy linguistic ordered weighted average operator are proposed. A consensus measure is then defined and a consensus reaching process is given which uses different identification and direction rules compared with the existing methods. A selection process is also described to rank the alternatives. Both processes are necessary to support stakeholders when making rational decisions. Finally, two simulated examples are given to verify the practicability of the proposed approach.

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

Abstract: This paper proposes a novel joint learning and densely-cooperative fusion (JL-DCF) architecture for RGB-D salient object detection. Existing models usually treat RGB and depth as independent information and design separate networks for feature extraction from each. Such schemes can easily be constrained by a limited amount of training data or over-reliance on an elaborately-designed training process. In contrast, our JL-DCF learns from both RGB and depth inputs through a Siamese network. To this end, we propose two effective components: joint learning (JL), and densely-cooperative fusion (DCF). The JL module provides robust saliency feature learning, while the latter is introduced for complementary feature discovery. Comprehensive experiments on four popular metrics show that the designed framework yields a robust RGB-D saliency detector with good generalization. As a result, JL-DCF significantly advances the top-1 D3Net model by an average of ~1.9% (S-measure) across six challenging datasets, showing that the proposed framework offers a potential solution for real-world applications and could provide more insight into the cross-modality complementarity task. The code will be available at https://github.com/kerenfu/JLDCF/.

Ammonia emission control in China would mitigate haze pollution and nitrogen deposition, but worsen acid rain

Abstract: China has been experiencing fine particle (i.e., aerodynamic diameters ≤ 2.5 µm; PM2.5) pollution and acid rain in recent decades, which exert adverse impacts on human health and the ecosystem. Recently, ammonia (i.e., NH3) emission reduction has been proposed as a strategic option to mitigate haze pollution. However, atmospheric NH3 is also closely bound to nitrogen deposition and acid rain, and comprehensive impacts of NH3 emission control are still poorly understood in China. In this study, by integrating a chemical transport model with a high-resolution NH3 emission inventory, we find that NH3 emission abatement can mitigate PM2.5 pollution and nitrogen deposition but would worsen acid rain in China. Quantitatively, a 50% reduction in NH3 emissions achievable by improving agricultural management, along with a targeted emission reduction (15%) for sulfur dioxide and nitrogen oxides, can alleviate PM2.5 pollution by 11-17% primarily by suppressing ammonium nitrate formation. Meanwhile, nitrogen deposition is estimated to decrease by 34%, with the area exceeding the critical load shrinking from 17% to 9% of China's terrestrial land. Nevertheless, this NH3 reduction would significantly aggravate precipitation acidification, with a decrease of as much as 1.0 unit in rainfall pH and a corresponding substantial increase in areas with heavy acid rain. An economic evaluation demonstrates that the worsened acid rain would partly offset the total economic benefit from improved air quality and less nitrogen deposition. After considering the costs of abatement options, we propose a region-specific strategy for multipollutant controls that will benefit human and ecosystem health.

The circular RNA ciRS-7 (Cdr1as) acts as a risk factor of hepatic microvascular invasion in hepatocellular carcinoma.

Abstract: Circular RNAs (circRNA) represent a novel class of widespread and diverse endogenous RNAs that regulate gene expression in mammals. microRNA-7 (miR-7) is a well-demonstrated suppressor of hepatocellular carcinoma (HCC). Recent studies have showed that one such circRNA, ciRS-7 (also termed as Cdr1as) was the inhibitor and sponge of miR-7 in the embryonic zebrafish midbrain and islet cells. However, the relationships among ciRS-7, miR-7 and clinical features of HCC remain to be clarified. Expression levels of ciRS-7, miR-7 and three miR-7-targeted mRNAs in 108 pairs of HCC and their matched non-tumor tissues were examined by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The protein production of these three miR-7-targeted mRNAs was further verified by Western blot. The relationship between ciRS-7 level and clinicopathological features as well as the recurrence of HCC patients was analyzed. The univariate and multivariate logistic regression analyses were used to detect the risk factors of hepatic microvascular invasion (MVI). The correlation among ciRS-7, miR-7 and miR-7-targeted mRNAs was evaluated using Spearman’s correlation test. There was no significant difference of ciRS-7 expression levels between the HCC tissues and the matched non-tumor tissues (0.67 ± 1.49 vs. 0.44 ± 0.45, p = 0.13), and the ciRS-7 levels in more than half of HCC tissues (65 out of 108, 60.2 %) were down-regulated when compared with their matched non-tumor tissues. However, the expression of ciRS-7 was significantly correlated with the following three clinicopathological characteristics of HCC patients: age <40 years (p = 0.02), serum AFP ≥400 ng/µl (p < 0.01) and hepatic MVI (p = 0.03). Meanwhile, up-regulated ciRS-7 expression was not only an independent risk factor of hepatic MVI but also had a capable predictive ability for MVI (AUC = 0.68, p = 0.001) at the cut-off value of 0.135. Furthermore, the expression of ciRS-7 in HCC tissues with concurrent MVI was inversely correlated with that of miR-7 (r = −0.39, p = 0.007) and positively related with that of two miR-7-targeted genes [PIK3CD (r = 0.55, p < 0.001) and p70S6K (r = 0.34, p = 0.021)]. In addition, the median recurrent time of patients from higher ciRS-7 level group was shorter than that of lower ciRS-7 group (18 vs. 25 months), but no significant difference was observed (p = 0.38). The expression levels of ciRS-7 were comparable between HCC and matched non-tumor tissues. However, the highly ciRS-7 expression in HCC tissues was significantly correlated with hepatic MVI, AFP level and younger age and thus partly related with the deterioration of HCC. Especially, ciRS-7 was one of the independent factors of hepatic MVI. These data suggested that ciRS-7 may be a promising biomarker of hepatic MVI and a novel therapy target for restraining MVI.