Cold damage has negatively impacted the yield, growth and quality of the edible cooking oil in Northern China and Brassica napus L.(rapeseed) planting areas decreased because of cold damage. In the present study we analyzed two Brassica napus cultivars of 16NTS309 (highly resistant to cold damage) and Tianyou2238 (cold sensitive) from Gansu Province, China using physiological, biochemical and cytological methods to investigate the plant's response to cold stress. The results showed that cold stress caused seedling dehydration, and the contents of malondialdehyde (MDA), relative electrolyte leakage and O 2 − and H 2 O 2 were increased in Tianyou2238 than 16NTS309 under cold stress at 4°C for 48 h, as well as the proline, soluble protein and soluble sugars markedly accumulated, and antioxidant enzymes of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) were higher in 16NTS309 compared with in Tianyou2238, which play key roles in prevention of cell damage. After exposure to cold stress, the accumulation of the blue formazan precipitate and reddish brown precipitate indicated that O 2 − and H 2 O 2 , respectively, were produced in the root, stem, and leaf were higher than under noncold conditions. Contents of O 2 − and H 2 O 2 in cultivar Tianyou2238 were higher than 16NTS309, this is consistent with the phenotypic result. To understand the specific distribution of O 2 − in the sub-cellular, we found that in both cultivars O 2 − signals were distributed mainly in cambium tissue, meristematic cells, mesophyll cytoplasm, and surrounding the cell walls of root, stem, leaves, and leaf vein by morphoanatomical analysis, but the quantities varied. Cold stress also triggered obvious ultrastructural alterations in leaf mesophyll of Tianyou2238 including the damage of membrane system, destruction of chloroplast and swelling of mitochondria. This study are useful to provide new insights about the physiological and biochemical mechanisms and cytology associated with the response of B. napus to cold stress for use in breeding cold-resistant varieties.

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Fuzzy best-worst method (BWM) has emerged as an efficient choice because of its comparison consistency to model the real-life and the consideration of fuzziness and uncertainties of decision-makers (DMs). However, how to extend the fuzzy BWM to group decision-making (GDM) environment has become an important topic because there are usually more than one decision-maker. For the GDM, decision makers may use different concepts to establish their individual assessment information due to the difference of cultural background and priori knowledge. To overcome this challenge, this article proposed a novel fuzzy best-worst multi-criteria group decision-making method to solve the GDM problem with multi-granular linguistic approach, which is an effective and promising technique to tackle this issue. In the proposed method, the selectable multi-granularity linguistic term sets (LTS) are firstly provided for experts to expressed their individual assessment information. Then, the improved fuzzy BWM is employed to calculate the weights of criteria with the form of fuzzy numbers. In current several studies using the BWM for group decision-making, only two unified best and worst criteria are given, which cannot reflect the evaluation of the best and worst criteria by different experts, resulting in the omission of information. Moreover, the difference between the best and worst criteria initially given and the experts' ideas will cause the experts to be inaccurate in the comparison of each criterion. Therefore, in this article, in order not to omit too much information, each expert will determine the best and the worst criteria. Each expert's assessment information which is based on his/her best and worst criteria is integrated into two vectors. What's more, an improved input-based consistency measurement is proposed, which can provide the DMs with a clear guideline on the revision of the inconsistent judgement(s). Finally, two examples are given to illustrate the effectiveness and applicability of the proposed method.INDEX TERMS Fuzzy best-worst method, group decision-making, linguistic assessment information, multi-granular fuzzy linguistic context, multi-criteria decision-making

Background: Post-stroke cognitive impairment (PSCI) is commonest clinical disorder in which peripheral cholinergic activity is important. Oleuropein (OLP) is polyphenol is present in olive oil. Here we evaluated the effect of OLP in cognitive dysfunction rats in post cerebral stroke model. Methods: The post cerebral stroke cognitive dysfunction PSD rat model was created by occlusion of transient middle cerebral artery. The rats were divided into 6 groups named, Sham + Vehicle, Sham + OLP (50 mg/kg), PSD rats + Vehicle, PSD rats + OLP (20, 50 or 100 mg/kg). The spatial learning was assessed by Morris water maze (MWM). The expression of choline acetyltransferase (ChAT), acetylcholine (ACH), extent of histone acetylation and phosphorylation of cAMP response element-binding protein (CREB) were evaluated by Western blot assay and immunofluorescence staining. Results: Treatment of OLP at various doses showed higher number of spontaneous and rewarded alterations and lesser percentage bias compared to vehicle treated PSD rats. OLP resulted in decreased levels of ChAT and ACH, whereas the degree of histone acetylation and phosphorylation of CREB improved in dose dependent pattern. Conclusion: treatment of OLP improved PSCI via increasing the phosphorylation of CREB and histone acetylation, thus attenuating cholinergic activity.

The electricity transmission and distribution tariff policy of the second supervision cycle in China has formulated a much better electricity transmission and distribution tariff supervision system. In this context, the research on the risk related to electricity transmission and distribution tariff regulation faced by power grid enterprises is helpful for power regulatory agencies and business operators to identify and avoid risks in time and promote the sustainable development of electric power industry. Firstly, the risk evaluation criteria system is established. Secondly, a risk evaluation model based on the best and worst method (BWM) and cloud model for electricity transmission and distribution tariff regulation is proposed. Finally, the risk level of power transmission and distribution tariff regulation faced by four provincial power grid enterprises is evaluated. The validity and practicability of the proposed model in this paper are proved by the empirical analysis.