Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

A hybrid DEMATEL-COPRAS method using interval-valued probabilistic linguistic term set for sustainable hydrogen fuel cell supplier of new energy vehicles.

With the continuous development of the global economy, global environmental pollution, climate degradation and global warming are becoming increasingly serious. In order to deal with the increasingly serious environmental problems, the government is vigorously supporting and promoting the development of new energy vehicles (NEVs). As the core unit of NEVs, one of the main challenges faced by hydrogen fuel cell (HFC) supplier is to select the best supplier for their business among all possible suppliers. Selecting the optimal supplier is a key decision in green supplier management. Therefore, it is extremely important and meaningful to select an optimal HFC supplier to provide power for NEVs. This paper proposes a new decision-making framework based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and Complex proportional assessment (COPRAS) method under interval-valued probabilistic linguistic environment to select the appropriate HFC supplier of NEVs. Firstly, this paper establishes the evaluation criteria system of HFC supplier assessment which is the synthesis of economical, environmental, social, technical, organisation and service aspects. Then, in order to express the uncertainty of expert decision-making, this paper uses interval-valued probabilistic linguistic term set (IVPLTS) to describe the evaluation information. Next, the interval-valued probabilistic linguistic term set decision-making trial and evaluation laboratory (IVPLTS-DEMATEL) method is applied to calculate the criteria weights. Moreover, this paper constructs the interval-valued probabilistic linguistic term set Complex Proportional Assessment (IVPLTS-COPRAS) model for the selection of HFC supplier of NEVs. Finally, a case in China with sensitivity analysis and comparison analysis are executed to illustrate the feasibility and validity of the proposed approach. This paper provides valuable references for investors and companies to select the most appropriate HFC supplier of NEVs under uncertain environment.

Source apportionment of heavy metals and their effects on the species diversity of plant communities in the Caizi Lake wetland, China.

This study investigated the effects of heavy metals on the species diversity of the Xinjian Dyke Wetland, an ecosystem where reclaimed farmlands are being transformed back into wetlands through the introduction of indigenous plants. The sources of soil heavy metals were analyzed, and correlation analyses were conducted to assess the relationships between heavy metal content and biodiversity indices. The results indicated that (1) the mean contents of Hg, Cd, Cu, Zn, As, Cr, and Pb were higher than the control values, with the content of Hg, Cd, Cu, and Zn exceeding the national standard; (2) the soil heavy metals mainly came from pesticides, chemical fertilizer, transportation, sewage irrigation, and the soil matrix; and (3) Hg and As were not significantly correlated with the diversity indices, but there was a highly positive correlation for Cu, Cr, and Pb, and a significant negative correlation for Zn and Cd. Collectively, our findings indicated that heavy metals have different effects on the plant species diversity inXinjian Dyke reconstruction area. The ecological restoration of wetlands from reclaimed farmlands should reasonably increase tolerant species and maximize the ecological niche differentiation of the species. Moreover, functionally redundant species should not be planted.

Selection of plastic solid waste treatment technology based on cumulative prospect theory and fuzzy DEMATEL.

Under the global implementation of a low-carbon economy, the treatment of municipal plastic solid waste (PSW) has become an important task to be solved urgently. In the actual decision-making process of PSW treatment, the evaluation information is usually fuzzy, and the decision-makers (DMs) are bounded rational. For selecting the most appropriate PSW treatment technology, we propose a multi-criteria decision-making (MCDM) method based on cumulative prospect theory and fuzzy decision-making trail and evaluation laboratory (DEMATEL). Firstly, we construct the criteria system of PSW treatment that consists of 9 sub-criteria from the perspectives of environment, economy, society, and technology. Then, considering the interdependences and interactions between these evaluation criteria and allowing multiple stakeholders to participate in decision-making, we propose a fuzzy DEMATEL method to deal with the fuzziness of evaluation in the decision-making process and determine the weights of the evaluation criteria. Subsequently, taking into account the different opinions of different stakeholders and psychological factors such as risk preference and loss aversion of stakeholders, we aggregate the evaluation information of different stakeholders and develop the PSW treatment alternatives to rank the orders by using the proposed multi-actor cumulative prospect theory (CPT) method. We study seven alternative processes for PSW treatment by the developed model, including landfill, recycling, pyrolysis, incineration, and the combination of landfilling and recycling, landfill and incineration, and recycling and pyrolysis. According to the ranking results, we find the combination of recycling and incineration is the best treatment alternative. We take the seven PSW treatment technologies in Shanghai as the case study to verify the effectiveness and feasibility of the proposed method. Through the sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method, we illustrate the effectiveness and superiority of the proposed method. This research provides significant references for the PSW treatment technology selection problems under uncertain environments and extends the methods in the decision-making field.

A multi-criteria group decision-making framework for investment assessment of offshore floating wind-solar-aquaculture project under probabilistic linguistic environment.

The offshore floating wind-solar-aquaculture (WSA) system with its advantages such as strong seakeeping ability, considerable power generation, and full utilization of ocean space and water resources will have a bright prospect in the future. In order to accelerate the sustainable development of the energy industry, it is very important to build a reasonable investment decision-making framework. Therefore, this paper aims to build a multi-criteria group decision-making (MCGDM) framework for investment decision-making of this project. Firstly, a comprehensive criteria system has been established. Secondly, probabilistic language term sets (PLTSs) are introduced to describe the uncertainty and fuzziness of decision information. Thirdly, the expert weight determination model is established based on the correlation measure and correlation coefficient of PLTSs, and the PL-fuzzy decision-making trial and evaluation laboratory (DEMATEL) method and the information entropy method are introduced to determine the subjective and objective weights of the criteria. In addition, considering the decision maker's psychological behavior, we choose probabilistic language the interactive and multiple attribute decision-making (TODIM) method to determine the optimal investment alternative. Finally, we apply the proposed framework to a case study. The results illustrate that the alternative A3 possesses the optimal comprehensive performance with the overall value is 1. Then, we conduct sensitivity analysis and comparative analysis to verify its robustness and feasibility. Scenario analysis in TODIM method showed that it is reasonable to express decision preference by setting different recession coefficients in the actual decision-making environment. This study can provide some reference for decision-makers, and also extend the method of decision-making field.

NF-κB1 p50 stabilizes HIF-1α protein through suppression of ATG7-dependent autophagy.

The function and underlying mechanisms of p50 in the regulation of protein expression is much less studied because of its lacking of transactivation domain. In this study, we discovered a novel function of p50 in its stabilization of hypoxia-inducible factor 1α (HIF-1α) protein under the condition of cells exposed to arsenic exposure. In p50-deficient (p50-/-) cells, the HIF-1α protein expression was impaired upon arsenic exposure, and such defect could be rescued by reconstitutional expression of p50. Mechanistic study revealed that the inhibition of autophagy-related gene 7 (ATG7)-dependent autophagy was in charge of p50-mediated HIF-1α protein stabilization following arsenic exposure. Moreover, p50 deletion promoted nucleolin (NCL) protein translation to enhance ATG7 mRNA transcription via directly binding transcription factor Sp1 mRNA and increase its stability. We further discovered that p50-mediated miR-494 upregulation gave rise to the inhibition of p50-mediated NCL translation by interacting with its 3'-UTR. These novel findings provide a great insight into the understanding of biomedical significance of p50 protein in arsenite-associated disease development and therapy.

Tetracycline Removal by Hercynite-Biochar from the Co-Pyrolysis of Red Mud-Steel Slag-Sludge.

The sludge-derived biochar is considered an effective emerging contaminants adsorbent for wastewater treatment. In this paper, red mud and steel slag (RMSS) was used for improving sludge dewaterability and enhancing the sludge-derived biochar adsorption capacity. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and a scanning electron microscope (SEM) were employed to comprehensively characterize the mineral composition, functional group, and morphology of the adsorbent. RMSS was able to improve the sludge dewatering performance by providing a skeleton structure to promote drainage and Fe(III) to decrease the Zeta potential. The dosage of 20 mg/g RMSS was able to reduce the specific resistance to filtration (SRF) and the Zeta potential of sludge from 1.57 × 1013 m/kg and -19.56 mV to 0.79 × 1013 m/kg and -9.10 mV, respectively. The co-pyrolysis of RMSS and sludge (2:8) induced the formation of biochar containing FeAl2O4 (PS80). The PS80 exhibited a large surface area (46.40 m2/g) and high tetracycline (TC) removal capacity (98.87 mg/g) when combined with H2O2 (PS80-H2O2). The adsorption process of TC onto PS80 and PS80-H2O2 was well described by the pseudo-first-order and pseudo-second-order kinetic model, indicating physisorption and chemisorption behavior. The results indicated that co-pyrolysis of RMSS sludge PS80-H2O2 could enhance the biochar adsorption capacity of TC, attributable to the degradation by ·OH generated by the heterogeneous Fenton reaction of FeAl2O4 and H2O2, the release of adsorbed sites, and the improvement of the biochar pore structure. This study proposed a novel method for the use of RMSS to dewater sludge as well as to induce the formation of FeAl2O4 in biochar with effective TC removal by providing a Fe and Al source, achieving a waste-to-resource strategy for the integrated management of industrial solid waste and sewage sludge.

Induction of RAC1 protein translation and MKK7/JNK-dependent autophagy through dicer/miR-145/SOX2/miR-365a axis contributes to isorhapontigenin (ISO) inhibition of human bladder cancer invasion.

Although our previous studies have identified that isorhapontigenin (ISO) is able to initiate autophagy in human bladder cancer (BC) cells by activating JNK/C-Jun/SESN2 axis and possesses an inhibitory effect on BC cell growth, association of autophagy directly with inhibition of BC invasion has never been explored. Also, upstream cascade responsible for ISO activating JNK remains unknown. Thus, we explored both important questions in the current study and discovered that ISO treatment initiated RAC1 protein translation, and its downstream kinase MKK7/JNK phosphorylation/activation, and in turn promoted autophagic responses in human BC cells. Inhibition of autophagy abolished ISO inhibition of BC invasion, revealing that autophagy inhibition was crucial for ISO inhibition of BC invasion. Consistently, knockout of RAC1 also attenuated induction of autophagy and inhibition of BC invasion by ISO treatment. Mechanistic studies showed that upregulation of RAC1 translation was due to ISO inhibition of miR-365a transcription, which reduced miR-365a binding to the 3'-UTR of RAC1 mRNA. Further study indicated that inhibition of miR-365a transcription was caused by downregulation of its transcription factor SOX2, while ISO-promoted Dicer protein translation increased miR-145 maturation, and consequently downregulating SOX2 expression. These findings not only provide a novel insight into the understanding association of autophagy induction with BC invasion inhibition by ISO, but also identify an upstream regulatory cascade, Dicer/miR145/SOX2/miR365a/RAC1, leading to MKK7/JNKs activation and autophagy induction.

Enormous Berry-Curvature-Based Anomalous Hall Effect in Topological Insulator (Bi,Sb)2Te3 on Ferrimagnetic Europium Iron Garnet beyond 400 K.

To realize the quantum anomalous Hall effect (QAHE) at elevated temperatures, the approach of magnetic proximity effect (MPE) was adopted to break the time-reversal symmetry in the topological insulator (Bi0.3Sb0.7)2Te3 (BST) based heterostructures with a ferrimagnetic insulator europium iron garnet (EuIG) of perpendicular magnetic anisotropy. Here we demonstrate large anomalous Hall resistance (RAHE) exceeding 8 Ω (ρAHE of 3.2 µΩ·cm) at 300 K and sustaining to 400 K in 35 BST/EuIG samples, surpassing the past record of 0.28 Ω (ρAHE of 0.14 µΩ·cm) at 300 K. The large RAHE is attributed to an atomically abrupt, Fe-rich interface between BST and EuIG. Importantly, the gate dependence of the AHE loops shows no sign change with varying chemical potential. This observation is supported by our first-principles calculations via applying a gradient Zeeman field plus a contact potential on BST. Our calculations further demonstrate that the AHE in this heterostructure is attributed to the intrinsic Berry curvature. Furthermore, for gate-biased 4 nm BST on EuIG, a pronounced topological Hall effect-like (THE-like) feature coexisting with AHE is observed at the negative top-gate voltage up to 15 K. Interface tuning with theoretical calculations has realized topologically distinct phenomena in tailored magnetic TI-based heterostructures.