•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
Objective
The effects of transcranial direct current stimulation (tDCS) in the treatment of knee osteoarthritis (KOA) is still unclear. The objective is to evaluate the efficacy and safety of tDCS in ...improving symptoms in patients with KOA.
Methods
The following electronic databases were searched for eligible randomized controlled trials (RCTs): PubMed, Embase, Web of Science, and the Cochrane Library. The search was performed from the inception dates to April 30, 2023. Data extraction and quality assessment were performed by two independent reviewers. Standard mean differences (SMDs) with 95% confidence intervals (95% CIs) for pooled data were calculated. A random‐effects model was used for the data analyses. The primary outcomes were pain and physical function. Secondary outcomes included stiffness, mobility performance, quality of life, pressure pain tolerance, and plasma levels of brain‐derived neurotrophic factor (BDNF).
Results
This meta‐analysis included 13 RCTs. tDCS was significantly associated with pain decrease compared with sham tDCS (SMD = −0.62, 95% CI −0.87 to −0.37, P < 0.00001). When comparing tDCS plus other non‐tDCS with sham tDCS plus other non‐tDCS, there was no longer a significant association with pain decrease (SMD = −0.45, 95% CI −1.08 to 0.17, P = 0.16). The changes in physical function were not significantly different between the tDCS and sham tDCS groups (SMD = −0.09, 95% CI −0.56 to 0.38, P = 0.71). When comparing tDCS plus other non‐tDCS with sham tDCS plus other non‐tDCS, there was still no significant association with improvement in physical function (SMD = −0.66, 95% CI −1.63 to 0.30, P = 0.18). There was no significant difference with improvement in stiffness (SMD = −0.21, 95% CI −0.77 to 0.34, P = 0.45), mobility performance (SMD = 4.58, 95% CI −9.21 to 18.37, P = 0.51), quality of life (SMD = −7.01, 95% CI −22.61 to 8.59, P = 0.38), and pressure pain tolerance (SMD = 0.30, 95% CI −0.09 to 0.69, P = 0.13). There was a statistically significant reduction in plasma levels of BDNF (SMD = −13.57, 95% CI −24.23 to −2.92, P = 0.01).
Conclusion
In conclusion, tDCS could significantly alleviate pain, but it might have no efficacy in physical function, stiffness, mobility performance, quality of life, and pressure pain tolerance among patients with KOA.
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•We propose the data-driven linguistic multi-attribute decision making.•We develop a data-driven method to learn personalized individual semantics.•We present a case study based on two real ...datasets.•We make a comparison with existing methods to justify the proposed model.
In parallel with the development of information and network technology, large amounts of data are being generated by the Internet, and data-driven methodologies are now often being used in decision-making. Recent studies have investigated personalized individual semantics (PIS) in various decision-making contexts to model a fact that words mean different things to different people. However, few studies have investigated PIS in the context of multi-attribute decision-making (MADM). In MADM, in addition to multi-attribute linguistic information, pre-existing classification of the alternatives is always present, which have not been considered in prior research. Most previous studies have simply demonstrated the feasibility of PIS methods with numerical examples using small-scale models, and not with realistic datasets. Therefore, in this study, we propose a data-driven learning model to analyze the PIS of decision makers to support a multi-attribute decision-making model that considers pre-existing classification of the alternatives. Specifically, we first propose a PIS multi-attribute learning function to define a general computation form for comprehensive evaluation of the value of alternatives. Then, considering this pre-existing classification of the alternatives, a PIS learning model is constructed by analyzing the relations between calculated values of alternatives and corresponding class assignments to obtain personalized numerical scales of linguistic terms for a decision maker. Finally, we present a case study based on two datasets and a comparison with other methods to justify the feasibility of the proposed model.
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The individual consistency and the consensus degree are two basic measures to conduct group decision making with reciprocal preference relations. The existing frameworks to manage individual ...consistency and consensus degree have been investigated intensively and follow a common resolution scheme composed by the two phases: the consistency improving process, and the consensus reaching process. But in these frameworks, the individual consistency will often be destroyed in the consensus reaching process, leading to repeat the consistency improving process, which is time consuming. In order to avoid repeating the consistency improving process, a consensus reaching process with individual consistency control is proposed in this paper. This novel consensus approach is based on the design of an optimization-based consensus rule, which can be used to determine the adjustment range of each preference value guaranteeing the individual consistency across the process. Finally, theoretical and numerical analysis are both used to justify the validity of our proposal.
Comparative linguistic expression preference relations (CLEPRs) are an effective tool to represent uncertain opinions of decision makers in group decision making (GDM). Nevertheless, multiple ...self-confidence levels are not considered by existing research on CLEPRs. Thus, this article proposes CLEPRs with self-confidence by considering multiple self-confidence levels and presents a way to measure their consistency level. Meanwhile, personalized individual semantics (PIS), indicating that words mean different things for different people, have been highlighted and investigated in the GDM with linguistic assessment information. Considering PIS in comparative linguistic expressions, this article proposes an optimization model based on the consistency-driven methodology to assess individual semantics in CLEPRs with self-confidence. Particularly, the PIS are described and addressed by setting different numerical scales of linguistic terms for different decision makers. Finally, an optimization-based consensus model is proposed to obtain a consensual collective solution, which seeks to minimize the information loss between the decision makers' preference relations with self-confidence and corresponding individual preference vectors.
Here, π-Extended BTD derivatives were successfully synthesized by Heck coupling reaction, which exhibited the the advantages of simplicity and efficiency, wild substrate scope, easily available ...substrates and high yield. The fluorescent probe PEG-BTDAr targeting LDs was successfully prepared by the nucleophilic substitution reaction between the Heck coupling reaction product 3 h and Amino polyethylene glycol monomethyl ether (Mn=2000). PEG-BTDAr exhibited the advantages of high selectivity, good stability and pH resistance. The use of PEG as a substrate gave PEG-BTDAr good biocompatibility. It was worth mentioning that PEG-BTDAr could not only track LDs in cells under different physiological conditions, but also distinguish between living and dead cells in biological systems.
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Inadequate reference databases in RNA‐seq analysis can hinder data utilization and interpretation. In this study, we have successfully constructed a high‐quality reference transcript dataset, ...ZjRTD1.0, for Zoysia japonica, a widely‐used turfgrass with exceptional tolerance to various abiotic stress, including low temperatures and salinity. This dataset comprises 113,089 transcripts from 57,143 genes. BUSCO analysis demonstrates exceptional completeness (92.4%) in ZjRTD1.0, with reduced proportions of fragmented (3.3%) and missing (4.3%) orthologs compared to prior datasets. ZjRTD1.0 enables more precise analyses, including transcript quantification and alternative splicing assessments using public datasets, which identified a substantial number of differentially expressed transcripts (DETs) and differential alternative splicing (DAS) events, leading to several novel findings on Z. japonica's responses to abiotic stresses. First, spliceosome gene expression influenced alternative splicing significantly under abiotic stress, with a greater impact observed during low‐temperature stress. Then, a significant positive correlation was found between the number of differentially expressed genes (DEGs) encoding protein kinases and the frequency of DAS events, suggesting the role of protein phosphorylation in regulating alternative splicing. Additionally, our results suggest possible involvement of serine/arginine‐rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) in generating inclusion/exclusion isoforms under low‐temperature stress. Furthermore, our investigation revealed a significantly enhanced overlap between DEGs and differentially alternatively spliced genes (DASGs) in response to low‐temperature stress, suggesting a unique co‐regulatory mechanism governing transcription and splicing in the context of low‐temperature response. In conclusion, we have proven that ZjRTD1.0 will serve as a reliable and useful resource for future transcriptomic analyses in Z. japonica.
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18.
Zeolite NPO‐Type Azolate Frameworks Zha, Xiangyi; Li, Xinhao; Al‐Omari, Abdulhadi A. ...
Angewandte Chemie International Edition,
September 26, 2022, Volume:
61, Issue:
39
Journal Article
Peer reviewed
Three‐membered rings (3‐rings) are an important structural motif in zeolite chemistry, but their formation remains serendipitous in reticular chemistry when designing zeolitic imidazolate frameworks ...(ZIFs). Herein, we report a design principle for constructing four new ZIFs, termed ZIF‐1001 to ‐1004, from tetrahedral ZnII centers (T), benzotriazolate (bTZ), and different functionalized benzimidazolates (RbIM) that adopt a new zeolite NPO‐type topology built from 3‐rings. Two factors were critical for this discovery: i) incorporating the bTZ linker within the structures formed 3‐rings due to a ∠(T−bTZ−T) angle of 120–130° reminiscent of the ∠(Ge−O−Ge) angle (130°) observed in germanate zeolite‐type structures having 3‐rings; and ii) RbIM guided the coordination chemistry of bTZ to bind preferentially in an imidazolate‐type mode. This series’ ability to selectively capture CO2 from high‐humidity flue gas and trap ethane from tail gas during shale gas extraction was demonstrated.
A new design principle for obtaining zeolitic imidazolate frameworks (ZIFs) with an underlying NPO built from three‐membered rings (3‐rings) is reported. Among the hundreds of unique ZIFs known, only a few have been discovered that are partially constructed from 3‐ring motifs. These findings provide a significant addition to the limited library of ZIF design principles to access attractive structural features for realizing practical function.
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•We analyze the origin and taxonomy of distributed linguistic representations.•We review the key elements of distributed linguistic representations in decision making.•We review the applications of ...distributed linguistic representations in decision making.•We propose ongoing challenges for distributed linguistic representations.
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Great efforts toward developing novel and efficient hole‐transporting materials are needed to further improve the device efficiency and enhance the cell stability of perovskite solar cells (PSCs). ...The poor film conductivity and the low carrier mobility of organic small‐molecule‐based hole‐transporting materials restrict their application in PSCs. This study develops an efficient and stable hole‐transporting material, tetrafluorotetracyanoquinodimethane (F4‐TCNQ)‐doped copper phthalocyanine‐3,4′,4′′,4′′′‐tetra‐sulfonated acid tetra sodium salt (TS‐CuPc) via a solution process, in planar structure PSCs. The p‐type‐doped TS‐CuPc film demonstrates improved film conductivity and hole mobility owing to the strong electron affinity of F4‐TCNQ. By the F4‐TCNQ tailoring, the composite film gives the highest occupied molecular orbital level as high as 5.3 eV, which is beneficial for hole extraction. In addition, the aqueous solution processed TS‐CuPc:F4‐TCNQ precursor is almost neutral with good stability for avoiding the electrode erosion. As a result, the fabricated PSCs employing TS‐CuPc:F4‐TCNQ as the hole‐transporting material exhibit a power conversion efficiency of 16.14% in a p–i–n structure and 20.16% in an n–i–p structure, respectively. The developed organic small molecule of TS‐CuPc provides the diversification of hole‐transporting materials in planar PSCs.
p‐Type‐doped copper phthalocyanine‐3,4′,4″,4″′‐tetra‐sulfonated acid tetra sodium salt (TS‐CuPc) by tetrafluorotetracyanoquinodimethane (F4‐TCNQ) with improved film conductivity and hole mobility is realized via a solution process. The composite film is used as a hole‐transporting layer in both p–i–n structure and n–i–p structure devices. A champion n–i–p structure device with a power conversion efficiency of 20.16% is obtained.
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