In linguistic large-scale group decision making (LSGDM), it is often necessary to achieve a consensus. Particularly, when computing with words and linguistic decision, we must keep in mind that words ...mean different things to different people. Therefore, to represent the specific semantics of each individual, we need to consider the personalized individual semantics (PIS) model in linguistic LSGDM. In this paper, we propose a consensus model based on PIS for LSGDM. Specifically, a PIS process to obtain the individual semantics of linguistic terms with linguistic preference relations is introduced. A consensus process based on PIS, including the consensus measure and feedback recommendation phases, is proposed to improve the willingness of decision makers who follow the suggestions to revise their preferences in order to achieve a consensus in linguistic LSGDM problems. The consensus measure defines two opposing consensus groups with respective acceptable and unacceptable consensus. In the feedback recommendation phase, a PIS-based clustering method to get decision makers with similar individual semantics is proposed. Recommendation rules design a feedback for decision makers with unacceptable consensus, finding suitable moderators from the decision makers with acceptable consensus based on cluster proximity.
Linguistic distribution expressions provide a flexible way for decision makers to express their opinions in linguistic decision making. When working with a linguistic distribution, words mean ...different things for different people, i.e., decision makers have personalized individual semantics (PISs) regarding words. Therefore, in this paper, we propose a consistency-driven methodology to manage distribution linguistic preference relations (DLPRs) with PISs. This methodology can not only estimate the ignorance elements in incomplete DLPRs but also obtain the personalized numerical meanings of linguistic expressions to decision makers. In this way, we can combine the characteristics of the personalized representation in linguistic decision making and guarantee the optimum consistency of incomplete DLPRs with ignorance elements. Detailed numerical and comparison analyses have been proposed to justify our proposal.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Interface strains and lattice distortion are inevitable issues during perovskite crystallization. Silane as a coupling agent is a popular connector to enhance the compatibility between inorganic and ...organic materials in semiconductor devices. Herein, a protonated amine silane coupling agent (PASCA‐Br) interlayer between TiO2 and perovskite layers is adopted to directionally grasp both of them by forming the structural component of a lattice unit. The pillowy alkyl ammonium bromide terminals at the upper side of the interlayer provide well‐matched growth sites for the perovskite, leading to mitigated interface strain and ensuing lattice distortion; meanwhile, its superior chemical compatibility presents an ideal effect on healing the under‐coordinated Pb atoms and halogen vacancies of bare perovskite crystals. The PASCA‐Br interlayer also serves as a mechanical buffer layer, inducing less cracked perovskite film when bending. The developed molecular‐level flexible interlayer provides a promising interfacial engineering for perovskite solar cells and their flexible application.
A protonated amino silane coupling agent as an interlayer is exploited on rigid and flexible substrates, which not only sets up well‐matched growth underlay but also serves as a structural component of the lattice units, leading to less‐distorted perovskite films, resulting in an obvious advance in device performance, stability, and mechanical tolerance in the corresponding flexible device.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
In hybrid organic–inorganic lead halide perovskite solar cells, the energy loss is strongly associated with nonradiative recombination in the perovskite layer and at the cell interfaces. Here, a ...simple but effective strategy is developed to improve the cell performance of perovskite solar cells via the combination of internal doping by a ferroelectric polymer and external control by an electric field. A group of polarized ferroelectric (PFE) polymers are doped into the methylammonium lead iodide (MAPbI3) layer and/or inserted between the perovskite and the hole‐transporting layers to enhance the build‐in field (BIF), improve the crystallization of MAPbI3, and regulate the nonradiative recombination in perovskite solar cells. The PFE polymer‐doped MAPbI3 shows an orderly arrangement of MA+ cations, resulting in a preferred growth orientation of polycrystalline perovskite films with reduced trap states. In addition, the BIF is enhanced by the widened depletion region in the device. As an interfacial dipole layer, the PFE polymer plays a critical role in increasing the BIF. This combined effect leads to a substantial reduction in voltage loss of 0.14 V due to the efficient suppression of nonradiative recombination. Consequently, the resulting perovskite solar cells present a power conversion efficiency of 21.38% with a high open‐circuit voltage of 1.14 V.
Perovskite solar cells based on polarized ferroelectric polymers are fabricated by doping the ferroelectric polymer into the perovskite layer with different polarizing electric fields and different doping concentrations, different polarized ferroelectric polymers' interlayers between the perovskite and the hole‐transporting layer, and both doping and interlayer. After these treatments, the fabricated devices show a maximum power conversion efficiency of 21.38%.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Organometallic halide perovskite films with good surface morphology and large grain size are desirable for obtaining high‐performance photovoltaic devices. However, defects and related trap sites are ...generated inevitably at grain boundaries and on surfaces of solution‐processed polycrystalline perovskite films. Seeking facial and efficient methods to passivate the perovskite film for minimizing defect density is necessary for further improving the photovoltaic performance. Here, a convenient strategy is developed to improve perovskite crystallization by incorporating a 2D polymeric material of graphitic carbon nitride (g‐C3N4) into the perovskite layer. The addition of g‐C3N4 results in improved crystalline quality of perovskite film with large grain size by retarding the crystallization rate, and reduced intrinsic defect density by passivating charge recombination centers around the grain boundaries. In addition, g‐C3N4 doping increases the film conductivity of perovskite layer, which is beneficial for charge transport in perovskite light‐absorption layer. Consequently, a champion device with a maximum power conversion efficiency of 19.49% is approached owing to a remarkable improvement in fill factor from 0.65 to 0.74. This finding demonstrates a simple method to passivate the perovskite film by controlling the crystallization and reducing the defect density.
Graphitic carbon nitride (g‐C3N4) is incorporated into the perovskite precursor solution to modify the perovskite film by controlling the perovskite crystallization, reducing the intrinsic defect density, and improving the film conductivity. As a result, a champion device with a maximum power conversion efficiency of 19.49% is approached.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Developing porous materials to overcome the trade‐off between adsorption capacity and selectivity for C2H2/CO2 separation remains a challenge. Herein, we report a stable HKUST‐1‐like MOF (ZJU‐50a), ...featuring large cages decorated with high density of supramolecular binding sites to achieve both high C2H2 storage and selectivity. ZJU‐50a exhibits one of the highest C2H2 storage capacity (192 cm3 g−1) and concurrently high C2H2/CO2 selectivity (12) at 298 K and 1 bar. Single‐crystal X‐ray diffraction studies on gas‐loaded ZJU‐50a crystal unveil that the incorporated supramolecular binding sites can selectively take up C2H2 molecule but not CO2 to result in both high C2H2 storage and selectivity. Breakthrough experiments validated its separation performance for C2H2/CO2 mixtures, providing a high C2H2 recovery capacity of 84.2 L kg−1 with 99.5 % purity. This study suggests a novel strategy of engineering supramolecular binding sites into MOFs to overcome the trade‐off for this separation.
We developed a novel strategy by engineering abundant supramolecular binding sites into a chemically stable HKUST‐1‐like MOF (ZJU‐50a) to achieve simultaneously high C2H2 storage and selectivity, breaking the trade‐off between adsorption capacity and selectivity for C2H2/CO2 separation.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
N6‐methyladenosine (m6A) modification regulatory proteins are involved in the development of many types of cancer. KIAA1429 serves as a scaffold in bridging the catalytic core components of the m6A ...methyltransferase complex. The role of KIAA1429 in gastric cancer and its related mechanism has not been reported upon. The expression of KIAA1429 was detected in human gastric cancer tissues and cell lines by quantitative real‐time polymerase chain reaction and western blot. The effects of KIAA1429 on gastric cancer proliferation were evaluated by cell counting kit assays, colony formation assays, flow cytometry assay, and in vivo experiments with nude mice. And messenger RNA (mRNA) high‐throughput sequencing, RNA immunoprecipitation assay (RIP), luciferase assay, and a rescue experiment were used to identify the relationship between KIAA1429 and its specific targeted gene, c‐Jun. We found that KIAA1429 was upregulated in gastric cancer tissues, and expressed lower in adjacent tissues. The upregulated KIAA1429 promoted proliferation and downregulated KIAA1429 was proved to inhibit proliferation of gastric cancer in vitro and in vivo. Then, we identified the potential KIAA1429 regulating gene as c‐Jun by mRNAs high‐throughput sequencing and RIP assay. By luciferase assay, we verified that KIAA1429 regulated the expression of c‐Jun in an m6A‐independent manner. Finally, the overexpression of c‐Jun rescued the inhibition of proliferation caused by KIAA1429 knockdown in gastric cancer cells. KIAA1429 could act as an oncogene in gastric cancer by stabilizing c‐Jun mRNA in an m6A‐independent manner. This highlights the functional role for KIAA1429 as a potential prognostic biomarker and therapeutic target in gastric cancer.
In this study, we provided in vitro and in vivo evidence that KIAA1429 played a key role in promoting gastric cancer by regulating c‐Jun expression in an m6A independent manner. This finding has the potential to develop a new therapeutic target for the treatment of gastric cancer.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The 2-tuple linguistic representation model is widely used as a basis for computing with words (CW) in linguistic decision making problems. Two different models based on linguistic 2-tuples (i.e., ...the model of the use of a linguistic hierarchy and the numerical scale model) have been developed to address term sets that are not uniformly and symmetrically distributed, i.e., unbalanced linguistic term sets (ULTSs). In this study, we provide a connection between these two different models and prove the equivalence of the linguistic computational models to handle ULTSs. Further, we propose a novel CW methodology where the hesitant fuzzy linguistic term sets (HFLTSs) can be constructed based on ULTSs using a numerical scale. In the proposed CW methodology, we present several novel possibility degree formulas for comparing HFLTSs, and define novel operators based on the mixed 0–1 linear programming model to aggregate the hesitant unbalanced linguistic information.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In computing with words, it has been stressed that words mean different things for different people, which entails that decision makers (DMs) have personalized individual semantics (PISs) attached to ...linguistic expressions in linguistic group decision making (GDM). In particular, the PISs of DMs are not fixed, and they will be changing during the consensus building process, which indicates the necessary of continual PIS learning. Therefore, in this article, we propose a continual PIS-learning-based consensus approach in linguistic GDM. Specifically, a continual PIS learning model with the consistency-driven methodology is proposed to update the PISs taking into account all the linguistic preference data given by DMs during the consensus process. Then, the consensus measurement and feedback recommendation based on PIS are developed to detect the consensus process. Finally, numerical examples and simulation analysis are presented to illustrate and justify the use of the continual PIS-learning-based consensus approach.
•We analyze the origin of feedback mechanism with minimum adjustment or cost (FMMA/C).•We review FMMA/C in classical group decision making problems.•We review FMMA/C in complex group decision making ...problems.•We propose some open problems on FMMA/C.
Consensus reaching process is a very powerful decision tool to eliminate the preference conflict in group decision making. In general, the consensus is achieved by the decision makers modifying their preferences (or opinions) toward a point of mutual consent, and the feedback mechanism aims to provide preference-modifications suggestions. In many situations, the preference-modifications mean cost and the resources for the consensus reaching process are limited. So, in the last decade, the feedback mechanism with minimum adjustment or cost (FMMA/C) has been developed and widely used in various group decision making contexts to improve consensus efficiency. In this review, we first analyze the origin and basic research paradigm of the FMMA/C. Then, we review the FMMA/C in two decision contexts: (1) the FMMA/C in classical group decision making problems, and (2) the FMMA/C in complex group decision making problems (e.g., social network, large-scale, and opinion dynamic group decision making problems). Finally, we identify research challenges and propose future research direction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
