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Abstract Suitable biomaterials with seed cells have promising potential to repair bone defects. However, bone marrow mesenchymal stem cells (BMSCs), one of the most common seed cells used in tissue engineering, cannot differentiate efficiently and accurately into functional osteoblasts. In view of this, a new tissue engineering technique combined with BMSCs and scaffolds is a major task for bone defect repair. Lentiviruses interfering with miR‐136‐5p or Smurf1 expression were transfected into BMSCs. The effects of miR‐136‐5p or Smurf1 on the osteogenic differentiation (OD) of BMSCs were evaluated by measuring alkaline phosphatase activity and calcium deposition. Then, the targeting relationship between miR‐136‐5p and Smurf1 was verified by bioinformatics website analysis and dual luciferase reporter assay. Then, a rabbit femoral condyle bone defect model was established. miR‐136‐5p/BMSCs/β‐TCP scaffold was implanted into the defect, and the repair of the bone defect was detected by Micro‐CT and HE staining. Elevating miR‐136‐5p‐3p or suppressing Smurf1 could stimulate OD of BMSCs. miR‐136‐5p negatively regulated Smurf1 expression. Overexpressing Smurf1 reduced the promoting effect of miR‐136‐5p on the OD of BMSCs. miR‐136‐5p/BMSCs/β‐TCP could strengthen bone density in the defected area and accelerate bone repair. SmurF1‐targeting miR‐136‐5p‐modified BMSCs combined with 3D‐printed β‐TCP scaffolds can strengthen osteogenic activity and alleviate bone defects.

Cardiotoxicity is a common side effect of cisplatin in cancer treatment, often complicating patient care. Tangeretin (TG), a natural compound found in citrus peel, shows promise in protecting against cisplatin-induced heart damage. Our study investigated TG’s protective effects both in cell culture and in animal models. TG effectively countered cisplatin-induced damage in heart cells, promoting mitochondrial health and glucose transporter expression. In animal studies, TG reduced markers of heart damage and improved cardiac function. Mechanistically, TG activated AMPK, reduced the inactivation of Acetyl-CoA Carboxylase (ACC) protein and inhibited p38 MAPK and prevented mitochondrial dysfunction and cell death. This research sheds light on TG’s potential in safeguarding the heart from cisplatin-induced harm.

Abstract Protonic ceramic fuel cells with high efficiency and low emissions exhibit high potential as next-generation sustainable energy systems. However, the practical proton conductivity of protonic ceramic electrolytes is still not satisfied due to poor membrane sintering. Here, we show that the dynamic displacement of Y3+ adversely affects the high-temperature membrane sintering of the benchmark protonic electrolyte BaZr0.1Ce0.7Y0.1Yb0.1O3−δ, reducing its conductivity and stability. By introducing a molten salt approach, pre-doping of Y3+ into A-site is realized at reduced synthesis temperature, thus suppressing its further displacement during high-temperature sintering, consequently enhancing the membrane densification and improving the conductivity and stability. The anode-supported single cell exhibits a power density of 663 mW cm−2 at 600 °C and long-term stability for over 2000 h with negligible performance degradation. This study sheds light on protonic membrane sintering while offering an alternative strategy for protonic ceramic fuel cells development.

Developing cathode materials with high performance in oxygen reduction reaction (ORR) is desirable for proton ceramic fuel cells (PCFCs) for energy conversion technology. BaCo0.4Fe0.4Zr0.1Y0.1O3–δ (BCFZY) is widely investigated as a cathode. Herein, BCFZY cathode is used as a paradigmatic example to study the impact of calcination temperature on microstructure, electronic structure, and ORR performance. Ion beam‐scanning electron microscopy indicates BCFZY prepared at 800 °C (BCFZY800) exhibits the largest specific surface area and cathode/electrolyte contact area. BCFZY800 exhibits a peak power density of 1.32 W cm−2 at 650 °C, which is 37% and 193% higher than that of BCFZY prepared at 700 °C (BCFZY700) and 1100 °C (BCFZY1100), respectively. Furthermore, BCFZY800 demonstrates high long‐term stability over 500 h. Soft X‐Ray absorption spectra indicate that the oxidation state of BCFZY800 is reduced, suggesting more catalytically active sites than those of BCFZY700 and BCFZY1100 after the ORR. This work provides a new understanding for enhanced PCFCs performance by proper porosity structure via fine‐tuning the calcination temperature.

Abstract Crystalline organic–inorganic hybrids, which exhibit colorimetric responses to ionizing radiation, have recently been recognized as promising alternatives to conventional X‐ray dosimeters. However, X‐ray‐responsive organic–inorganic hybrids are scarce and the strategy to fine‐tune their detection sensitivity remains elusive. Herein, an unprecedented mixed‐ligand strategy is reported to modulate the X‐ray detection efficacy of organic–inorganic hybrids. Deliberately blending the stimuli‐responsive terpyridine carboxylate ligand (tpc−) and the auxiliary pba− group with different ratios gives rise to two OD thorium‐bearing clusters (Th‐102 and Th‐103) and a 1D coordination polymer (Th‐104). Notably, distinct X‐ray sensitivity is evident as a function of molar ratio of the tpc− ligand, following the trend of Th‐102 > Th‐103 > Th‐104. Moreover, Th‐102, which is exclusively built from the tpc− ligands with the highest degree of π–π interactions, exhibits the most sensitive radiochromic and fluorochromic responses toward X‐ray with the lowest detection limit of 1.5 mGy. The study anticipates that this mixed‐ligand strategy will be a versatile approach to tune the X‐ray sensing efficacy of organic–inorganic hybrids.

Abstract Designing efficient catalyst for the oxygen evolution reaction (OER) is of importance for energy conversion devices. The anionic redox allows formation of O-O bonds and offers higher OER activity than the conventional metal sites. Here, we successfully prepare LiNiO2 with a dominant 3d 8 L configuration (L is a hole at O 2p) under high oxygen pressure, and achieve a double ligand holes 3d 8 L 2 under OER since one electron removal occurs at O 2p orbitals for NiIII oxides. LiNiO2 exhibits super-efficient OER activity among LiMO2, RMO3 (M = transition metal, R = rare earth) and other unary 3d catalysts. Multiple in situ/operando spectroscopies reveal NiIII→NiIV transition together with Li-removal during OER. Our theory indicates that NiIV (3d 8 L 2) leads to direct O-O coupling between lattice oxygen and *O intermediates accelerating the OER activity. These findings highlight a new way to design the lattice oxygen redox with enough ligand holes created in OER process.

Membranes with fast and selective ion transport are essential for electrochemical processes. Here the authors provide mechanistic insights into the structures of metal-ion coordinated polybenzimidazole membranes and the preferential K+ transport, and their application in an alkaline zinc-iron flow battery.

Abstract MXene‐supported noble metal alloy catalysts exhibit remarkable electrocatalytic activity in various applications. However, there is no facile one‐step method for synthesizing these catalysts, because the synthesis of MXenes requires a strongly oxidizing environment and the preparation of platinum nanoalloys requires a strongly reducing environment and high temperatures. Hence, achieving coupling in one step is extremely challenging. In this paper, a straightforward one‐step molten salt method for preparing MXene‐supported platinum nanoalloy catalysts is proposed. The molten salt acts as the reaction medium to dissolve the transition metals and platinum ions at high temperatures. Transition metal ions oxidize the A‐site element from its MAX precursor at high temperatures, and the resulting transition metals further reduce platinum ions to form alloys. By coupling Al oxidation and platinum ion reduction using a molten salt solvent, this method directly converts Ti3AlC2 to a Pt‐M@Ti3C2Tx catalyst (where M denotes the transition metal). It further offers the possibility of extending the Pt‐M phase to binary, ternary, or quaternary platinum‐containing nanoalloys and converting the Al‐containing MAX phase to Ti2AlC and Ti3AlCN. Due to the strong interfacial interaction, the as‐prepared Pt‐Co@Ti3C2Tx is superior to commercial Pt/C (20 wt.%) in the hydrogen evolution reaction.

Cisplatin is the most widely used anticancer chemotherapy drug at present. However, its severe nephrotoxic side effects limit the clinical application. This study aimed to investigate the potential protective mechanism of arabinogalactan (AG) on acute kidney injury (AKI) induced by cisplatin in mice. Firstly, 105 potential targets of AG were predicted by using the SwissTargetPrediction database, 25,183 kidney disease targets were obtained by searching 5 disease databases, and 100 cross-target targets were obtained by drawing a Venn diagram. We constructed the “AG-Key target” interaction network and PPI protein interaction network of cross-targets and screened out 21 core targets. Through the GO and KEGG enrichment analysis of the core targets, we can found that the core targets involved a total of 1254 biological functions and 56 signaling pathways, including the apoptosis signaling pathway. By establishing an animal model in vivo, we found that pretreatment with AG at doses of 200 and 400 mg/kg could decrease the kidney index, such as serum creatinine (CRE), and blood urea nitrogen (BUN) levels induced by cisplatin, and reduce the kidney histopathology injury. Importantly, AG could inhibit the formation of metaldehyde (MDA) and 4-hydroxynonenal (4-HNE) in the kidney tissues and reduce the oxidative stress injury induced by cisplatin. Meanwhile, AG also restored the expression of anti-apoptotic proteins Bcl-2 and Bcl-xL and decreased the expression of pro-apoptotic proteins Bax and Bad in cisplatin-induced renal tissues. Finally, AG could further reduce cisplatin-induced kidney cell apoptosis.

As potential nuclear waste host matrices, two series of uranium-doped Nd2Zr2O7 nanoparticles were successfully synthesized using an optimized molten salt method in an air atmosphere. Our combined X-ray diffraction, Raman and X-ray absorption fine-structure (XAFS) spectroscopy studies reveal that uranium ions can precisely substitute the Nd site to form an Nd2–xUxZr2O7+δ (0 ≤ x ≤ 0.2) system and the Zr site to form an Nd2Zr2–yUyO7+δ (0 ≤ y ≤ 0.4) system without any impurity phase. With increasing U concentration, there is a phase transition from pyrochlore (Fd3m) to defect fluorite (Fm3m) structures in both series of U-doped Nd2Zr2O7. The XAFS analysis indicates that uranium exists in the form of high-valent U6+ in all samples. To balance the extra charge for substituting Nd3+ or Zr4+ by U6+, additional oxygen is introduced accompanied by a large structural distortion; however, the Nd2Zr1.6U0.4O7+δ sample with high U loading (20 mol%) still maintains a regular fluorite structure, indicating the good solubility of the Nd2Zr2O7 host for uranium. This study is, to the best of our knowledge, the first systematic study on U-incorporated Nd2Zr2O7 synthesized via the molten salt method and provides convincing evidence for the feasibility of accurately immobilizing U at specific sites.

Radiation dosimeters that measure ionizing radiations over a broad range and allow for direct readout are desirable. Here, the authors present a dual-mode photochromic thorium-based metal-organic nanocluster that enables direct visible colorimetric dosimetry of UV, β-ray, and γ-ray radiation.

Solid oxide electrolysis cells (SOECs) have great application prospects because of their excellent performance, but the long-term applications of the stacks are restricted by the structural degradation under the high-temperature conditions. Therefore, an SOEC degradation model is developed and embedded in a process model of the high-temperature steam electrolysis (HTSE) system to investigate the influence of the stack degradation at the system level. The sensitivity analysis and optimization were carried out to study the influence factors of the stack degradation and system hydrogen production efficiency and search for the optimal operating conditions to improve the hydrogen production efficiency and mitigate the stack degradation. The analysis results show that the high temperature and large current density can accelerate the stack degradation but improve the hydrogen production efficiency, while the high temperature gradually becomes unfavorable in the late stage. The low air-to-fuel feed ratio is beneficial to both the degradation rate and hydrogen production efficiency. The results show that the optimization method can improve the hydrogen production efficiency and inhibit the stack degradation effectively. Moreover, part of the hydrogen production efficiency has to be sacrificed in order to obtain a lower stack degradation rate.

High efficiency, raw material availability, and compatibility with downstream systems will enable the Solid Oxide Electrolysis Cell (SOEC) to play an important role in the future energy transition. However, the SOEC stack’s performance should be improved further by utilizing a novel flow-field design, and the channel shape is a key factor for enhancing gas transportation. To investigate the main effects of the novel channel design with fewer calculations, we assumed ideal gas laminar flows in the cathode channel. Furthermore, the cathode support layer thickness and electrical contact resistance are ignored. The conventional channel flow is validated first with mesh independence, and then the performance difference between the conventional and novel designs is analyzed using COMSOL Multiphysics. The process parameters such as velocity, pressure, current density, and mole concentration are compared between the conventional and novel designs, demonstrating that the novel design significantly improves electrolysis efficiency. Furthermore, it directly increased the concentration of product hydrogen in the novel channel. In addition to enhancing convection and diffusion of reaction gases in neighboring channels, the simple structure makes it easy to manufacture, which is advantageous for accelerating commercial use of the novel design.

Facile and reliable screening of efficient electrocatalysts is important for energy conversion technologies such as water splitting. Here, authors introduce A-site ionic electronegativity as a descriptor to understand the hydrogen-evolution activities of cobalt-based perovskites.

Understanding the catalytic mechanism of bimetallic nanocatalysts remains challenging. Here the authors demonstrate that the d-orbital charge on the surface of Pd in a well-defined AuPd nanoalloy serves as a descriptor to the adsorbate states and hence the catalytic performance.

ABSTRACT: The South Yellow Sea Basin is a large sedimentary basin superimposed by the Mesozoic-Paleozoic marine sedimentary basin and the Mesozoic-Cenozoic terrestrial sedimentary basin, where no oil and gas fields have been discovered after exploration for 58 years. After the failure of oil and gas exploration in terrestrial basins, the exploration target of the South Yellow Sea Basin turned to the marine Mesozoic-Paleozoic strata. After more than ten years’ investigation and research, a lot of achievements have been obtained. The latest exploration obtained effective seismic reflection data of deep marine facies by the application of seismic exploration technology characterized by high coverage, abundant low-frequency components and strong energy source for the deep South Yellow Sea Basin. In addition, some wells drilled the Middle-Upper Paleozoic strata, with obvious oil and gas shows discovered in some horizons. The recent petroleum geological research on the South Yellow Sea Basin shows that the structure zoning of the marine residual basin has been redetermined, the basin structure has been defined, and 3 seismic reflection marker layers are traceable and correlatable in the residual thick Middle-Paleozoic strata below the continental Meso-Cenozoic strata in the South Yellow Sea Basin. Based on these, the seismic sequence of the marine sedimentary strata was established. According to the avaliable oil and gas exploration and research, the marine Mesozoic-Paleozoic oil and gas prospects of the South Yellow Sea were predicted as follows. (1) The South Yellow Sea Basin has the same sedimentary formation and evolution history during the sedimentary period of the Middle-Paleozoic marine basin with the Sichuan Basin. (2) There are 3 regional high-quality source rocks. (3) The carbonate and clastic reservoirs are developed in the Mesozoic-Paleozoic strata. (4) The three source-reservoir-cap assemblages are relatively intact. (5) The Laoshan Uplift is a prospect area for the Lower Paleozoic oil and gas, and the Wunansha Uplift is one for the marine Upper Paleozoic oil and gas. (6) The Gaoshi stable zone in the Laoshan Uplift is a favorable zone. (7) The marine Mesozoic-Paleozoic strata in the South Yellow Sea Basin has the geological conditions required to form large oil and gas fields, with remarkable oil and gas resources prospect. An urgent problem to be addressed now within the South Yellow Sea Basin is to drill parametric wells for the Lower Paleozoic strata as the target, to establish the complete stratigraphic sequence since the Paleozoic period, to obtain resource evaluation parameters, and to realize the strategic discovery and achieve breakthrough in oil and gas exploration understanding.©2019 China Geology Editorial Office.

Ni nanocatalysts produced through exsolution have shown strong resistance to particle sintering and carbon coking in a beneficial dry reforming of methane (DRM) reaction utilizing greenhouse gases such as CH4 and CO2. However, most of the existing oxide supports for exsolution have been limited to perovskite oxide, while studies on fluorite support have been rarely conducted due to the limited solubility despite its excellent redox stability. Here we demonstrate that 3 ​mol% Ni can be successfully dissolved into the yttria-stabilized zirconia (YSZ) lattice and be further exsolved to the surface in a reducing atmosphere. The YSZ decorated with exsolved Ni nanoparticles shows enhanced catalytic activity for DRM reaction compared to the conventional cermet type of bulk Ni-YSZ. Moreover, the catalytic activity is extremely stable for about 300 ​h without significant degradation. Overall results suggest that the YSZ-based fluorite structure can be utilized as one of the support oxides for exsolution.

With the development of the Internet and big data, more and more consumer behavior data are used in different forecasting problems, which greatly improve the performance of prediction. As the main travel tool, the sales of automobiles will change with the variations of the market and the external environment. Accurate prediction of automobile sales can not only help the dealers adjust their marketing plans dynamically but can also help the economy and the transportation sector make policy decisions. The automobile is a product with high value and high involvement, and its purchase decision can be affected by its own attributes, economy, policy and other factors. Furthermore, the sample data have the characteristics of various sources, great complexity and large volatility. Therefore, this paper uses the Support Vector Regression (SVR) model, which has global optimization, a simple structure, and strong generalization abilities and is suitable for multi-dimensional, small sample data to predict the monthly sales of automobiles. In addition, the parameters are optimized by the Grey Wolf Optimizer (GWO) algorithm to improve the prediction accuracy. First, the grey correlation analysis method is used to analyze and determine the factors that affect automobile sales. Second, it is used to build the GWO-SVR automobile sales prediction model. Third, the experimental analysis is carried out by using the data from Suteng and Kaluola in the Chinese car segment, and the proposed model is compared with the other four commonly used methods. The results show that the GWO-SVR model has the best performance of mean absolute percentage error (MAPE) and root mean square error (RMSE). Finally, some management implications are put forward for reference.

Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis. First published online 28 February 2020

ABSTRACT: In order to make a breakthrough in Mesozoic-Paleozoic shale gas exploration in the South Yellow Sea Basin, a comparison of the preservation conditions was made within the Barnett shale gas reservoirs in the Fortworth Basin, the Jiaoshiba shale gas reservoirs in Sichuan Basin and potential shale gas reservoirs in Guizhou Province. The results show that the “Sandwich” structure is of great importance for shale gas accumulation. Therein to, the “Sandwich” structure is a kind of special reservoir-cap rock assemblage which consist of limestone or dolomite on the top, mudstone or shale layer in the middle and limestone or dolomite at the bottom. In consideration of the Mesozoic-Paleozoic in the Lower Yangtze, and Laoshan Uplift with weak Paleozoic deformation and thrust fault sealing on both flanks of the Laoshan Uplift, a conclusion can be drawn that the preservation conditions of shale gas probably developed “Sandwich” structures in the Lower Cambrian and Permian, which are key layers for the breakthrough of shale gas in the South Yellow Sea. Moreover, the preferred targets for shale gas drilling probably locate at both flanks of the Laoshan Uplift.

A circular economy (CE) is proposed to mitigate resource shortage and environmental pollution. Given the inevitable conflict between the new development mode and traditional economic benefits, practical experience shows that CE implementation needs the support of outside forces, such as government policy interventions or environmental organisations’ propaganda guidance. On the basis of existing studies, the present work establishes a systematic economic model in accordance with the characteristics, objectives and principles of CE. The equilibrium solution and critical condition of government and non-government participation models are obtained through game analysis. We select the industrial waste water circulation of some provinces in China to illustrate the feasibility and effectiveness of the proposed model. Overall, our results indicate that the gap between the critical price and unit processing cost determines the promotion of CE and government intervention. Moreover, government intervention is critical to building a waste management department in its early stage. First published online 27 November 2019

Abstract Various types of polyoxometalates (POMs) have been synthesized since the 19th century, but their assortment has been mostly limited to Groups 5 and 6 metals. Herein, a new family of POMs composed of a carbon group element as the addenda atoms with two distinct phases, LnPbOClO4‐1 (Ln = Sm to Ho, Y) and LnPbOClO4‐2 (Ln = Er and Tm) is reported. Both structures are built from [Ln6O8] rare‐earth metal hexamers being incorporated in [Pb18O32]/[Pb12O24] polyplumbites, and unbound perchlorates as charge‐balancing anions. Impressively, YPbOClO4‐1 and ErPbOClO4‐2 exhibit exceptional uptake capacities (434.7 and 427.7 mg g−1) toward ReO4−, a chemical surrogate for the key radioactive fission product in the nuclear fuel cycle 99TcO4−, which are the highest values among all inorganic anion‐exchange materials reported until now. The sorption mechanism is clearly elucidated and visualized by single‐crystal‐to‐single‐crystal structural transformation from ErPbOClO4‐2 to a perrhenate‐containing complex ErPbOReO4, revealing a unique ReO4− uptake selectivity driven by specific interaction within Pb···O‐ReO3− bonds.

With the development of the social economy and an enlarged volume of information, the application of multiple-criteria decision making (MCDM) has become increasingly wide and deep. As a brilliant MCDM technique, the best–worst method (BWM) has attracted many scholars’ attention because it can determine the weights of criteria with less comparison time and higher consistency between judgments than analytic hierarchy process. However, the effectiveness of the BWM is based on complete comparison information among criteria. Considering the fact that the decision makers may have limited time and energy to study all criteria, they cannot construct a complete comparison system. In this paper, we propose a novel MCDM method named BW-MaxEnt that combines BWM and the maximum entropy method (MaxEnt) to identify the weights of unfamiliar criteria with incomplete decision information. The model can be translated into a convex optimization problem that can be solved effectively and has an overall optimal solution. Finally, a practical application concerning the procurement of GPU workstations illustrates the feasibility of the proposed BW-MaxEnt method.

Online reviews of hotels reflect tourist perception and evaluation, which are becoming an important perspective of studying hotel selection. In this paper, we prefer to use a probabilistic linguistic term set (PLTS) to fully reveal evaluation grades and the corresponding probability distribution in the online reviews of hotels. In this way, we propose a novel stochastic dominance-based approach based on stochastic dominance degrees of PLTSs and a stochastic multi-criteria acceptability analysis (SMAA) method that tolerates missing information. Among them, first-, second-, and third-order stochastic dominance degrees of PLTSs are calculated on the premise that the dominance relationships between PLTSs can be defined based on first-, second-, and third-order stochastic dominance rules of PLTSs. Based on these basic researches, five hotels are selected as alternatives in our case study to verify the validity and feasibility of the proposed approach. In the end, data analysis illustrates the influence of parameter and linguistic scale functions and how to choose appropriate parameter values. Furthermore, comparative analysis with other methods shows the stability of the proposed approach.

With the development of the urbanization process, the demand for water resources has increased significantly, but the pollution of water resources has caused serious problems. These changes pose a potential threat to water resource carrying capacity in many regions. However, how to determine the areas of highest risk in water resource carrying capacity is an urgent problem which remains to be solved. Resounding to these circumstances, this study establishes a TODIM-PROMETHEE Ⅱ (An acronym in Portuguese for interactive and multiple attribute decision making- preference ranking organization method for enrichment evaluation Ⅱ) based decision support framework to address this issue for the regions of intensive governance, thereby providing support. In this framework, a novel theoretical concept, namely probabilistic linguistic Z-numbers, is proposed to describe group decision information. The related knowledge of probabilistic linguistic Z-numbers is developed, including a comparison method, distance, and operational rules. Subsequently, a case study involving the evaluation of water resource carrying capacity is conducted to demonstrate the feasibility of the decision support model, followed by sensitivity analysis, comparison analysis, and discussion. The findings demonstrate that the constructed framework demonstrates great performance to address this issue.

In recent years, hesitant fuzzy sets and neutrosophic sets have aroused the interest of researchers and have been widely applied to multi-criteria decisionmaking problems. The operations of multi-valued neutrosophic sets are introduced and a comparison method is developed based on related research of hesitant fuzzy sets and intuitionistic fuzzy sets in this paper. Furthermore, some multi-valued neutrosophic number aggregation operators are proposed and the desirable properties are discussed as well. Finally, an approach for multi-criteria decision-making problems was explored applying the aggregation operators. In addition, an example was provided to illustrate the concrete application of the proposed method.

Pedestrian is an important factor for traffic safety and capacity in the sections mixed with bicycle. It is important for improving active safety to implement timely pedestrian safety warning under the condition of Internet of pedestrian and bicycle. The mutual influence of pedestrian and its surrounding traffic participants in mixed pedestrian-bicycle sections was comprehensively analyzed, and the phase of pedestrian-bicycle traffic was partitioned and reduced on the basis of previous researches and phase-field coupling theory. Fuzzy logic method was used to build the pedestrian movement intention identification model. The pedestrian safety and the satisfaction for walking speed and space were synthetically considered in this model. The experimental verifications show that the result of pedestrian movement intention identification model is consistent with the actual situation, and this study can provide theoretical support for the realization of the pedestrian active safety under the condition of Internet of Things.

The financial risk not only affects the development of the company itself, but also affects the economic development of the whole society; therefore, the financial risk assessment of company is an important part. At present, numerous methods of financial risk assessment have been researched by scholars. However, most of the extant methods neither integrated fuzzy sets with quantitative analysis, nor took into account the historical data of the past few years. To settle these defects, this paper proposes a novel financial risk assessment model for companies based on heterogeneous multiple-criteria decision-making (MCDM) and historical data. Subjective and objective indexes are comprehensively taken into consideration in the financial risk assessment index system of the model, which combines fuzzy theory with quantitative data analysis. Moreover, the assessment information obtained from historical financial information of company, credit rating agency and decision makers, including crisp numbers, triangular fuzzy numbers and neutrosophic numbers. Furthermore, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to determine the ranking order of companies according to their financial risk. Finally, an empirical study of financial risk assessment for companies is conducted, and the results of comparative analysis and sensitivity analysis suggest that the proposed model can effectively and reliably obtain the company with the lowest financial risk.

Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.

To promote the development of nuclear power project in inland China, a specialized multi-criteria decision support framework is constructed for the site selection of inland nuclear power plants in this work. The best worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), and technique for order performance by similarity to ideal solution (TOPSIS) are integrated with Z-numbers, namely Z-BWM, Z-DEMATEL, and Z-TOPSIS. Z-BWM and Z-DEMATEL are combined to produce the weights of criteria, and an extended Z-TOPSIS is utilized to determine the ranking of all alternatives. Finally, a case study is performed in Hunan province to demonstrate the practicability of the proposed decision support framework. The robustness and feasibility of the proposed method are shown by an in-depth analysis of the decision results.

Single-valued neutrosophic sets (SVNSs), which involve in truth-membership, indeterminacy-membership and falsity-membership, play a significant role in describing the decision-makers’ preference information. In this study, a single-valued neutrosophic multi-criteria decision-making (MCDM) approach is developed based on Shapley fuzzy measures and power aggregation operator that takes a correlative relationship among criteria into account and also simultaneously reduces the effects of abnormal preference information. Firstly, two aggregation operators, namely, generalized weighted single-valued neutrosophic power Shapley Choquet average (GWSVNPSCA) operator and generalized weighted single-valued neutrosophic power Shapley Choquet geometric (GWSVNPSCG) operator, are accordingly defined, and the corresponding properties are discussed as well. Secondly, based on the proposed aggregation operators, an integrated MCDM approach is proposed to effectively solve single-valued neutrosophic problems where the weight information is incompletely known. A programming model is constructed to obtain the optimal Shapley fuzzy measure. Next, the proposed operators are utilized to aggregate the decision-makers’ preference information. Finally, a theoretical example with tourism attraction selection is provided to examine the efficacy of the developed approach, in which the results is found reasonable and credible.

This paper presents a fuzzy multi-criteria decision-making (FMCDM) approach based on cloud model and prospect theory. In addition, a reference point selection method is developed according to the evaluations of the potential customer or similar consumers regarding certain items. An example of purchasing decision problems is provided in order to illustrate the applicability of the proposed approach. A comparative analysis of the proposed approach is also performed in order to verify its feasibility.

This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the proposed weighted correlation coefficient measure of INSs, a decision-making method is developed, which takes into account the influence of the evaluations’ uncertainty and both the objective and subjective weights.

In recent years, hesitant fuzzy sets (HFSs) and neutrosophic sets (NSs) have become a subject of great interest for researchers and have been widely applied to multi-criteria group decision-making (MCGDM) problems. In this paper, multi-valued neutrosophic sets (MVNSs) are introduced, which allow the truth-membership, indeterminacy- membership and falsity-membership degree have a set of crisp values between zero and one, respectively. Then the operations of multi-valued neutrosophic numbers (MVNNs) based on Einstein operations are defined, and a comparison method for MVNNs is developed depending on the related research of HFSs and Atanassov's intuitionistic fuzzy sets (IFSs). Furthermore, the multi-valued neutrosophic power weighted average (MVNPWA) operator and the multi-valued neutrosophic power weighted geometric (MVNPWG) operator are proposed and the desirable properties of two operators are also discussed. Finally, an approach for solving MCGDM problems is explored by applying the power aggregation operators, and an example is provided to illustrate the application of the proposed method, together with a comparison analysis.

Soft sets have been regarded as a useful mathematical tool to deal with uncertainty. In recent years, many scholars have shown an intense interest in soft sets and extended standard soft sets to intuitionistic fuzzy soft sets, interval-valued fuzzy soft sets, and generalized fuzzy soft sets. In this paper, hesitant fuzzy soft sets are defined by combining fuzzy soft sets with hesitant fuzzy sets. And some operations on hesitant fuzzy soft sets based on Archimedean t-norm and Archimedean t-conorm are defined. Besides, four aggregation operations, such as the HFSWA, HFSWG, GHFSWA, and GHFSWG operators, are given. Based on these operators, a multicriteria group decision making approach with hesitant fuzzy soft sets is also proposed. To demonstrate its accuracy and applicability, this approach is finally employed to calculate a numerical example.

The weighted geometric averaging (WGA) operator and the ordered weighted geometric (OWG) operator are two of most basic operators for aggregating information. But these two operators can only be used in situations where the given arguments are exact numerical values. In this paper, we first propose some new geometric aggregation operators, such as the log-normal distribution weighted geometric (LNDWG) operator, log-normal distribution ordered weighted geometric (LNDOWG) operator and log-normal distribution hybrid geometric (LNDHG) operator, which extend the WGA operator and the OWG operator to accommodate the stochastic uncertain environment in which the given arguments are log-normally distributed random variables, and establish various properties of these operators. Then, we apply the LNDWG operator and the LNDHG operator to develop an approach for solving multi-criteria group decision making (MCGDM) problems, in which the criterion values take the form of log-normally distributed random variables and the criterion weight information is known completely. Finally, an example is given to illustrate the feasibility and effectiveness of the developed method.

The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based on t-conorms and t-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einstein t-conorms and t-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis.

As a generalization of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets have been developed to represent uncertain, imprecise, incomplete, and inconsistent information existing in the real world. And interval neutrosophic sets (INSs) have been proposed exactly to address issues with a set of numbers in the real unit interval, not just a specific number. However, there are fewer reliable operations for INSs, as well as the INS aggregation operators and decision making method. For this purpose, the operations for INSs are defined and a comparison approach is put forward based on the related research of interval valued intuitionistic fuzzy sets (IVIFSs) in this paper. On the basis of the operations and comparison approach, two interval neutrosophic number aggregation operators are developed. Then, a method for multicriteria decision making problems is explored applying the aggregation operators. In addition, an example is provided to illustrate the application of the proposed method.

Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

We investigate the dynamic stochastic multicriteria decision making (SMCDM) problems, in which the criterion values take the form of log-normally distributed random variables, and the argument information is collected from different periods. We propose two new geometric aggregation operators, such as the log-normal distribution weighted geometric (LNDWG) operator and the dynamic log-normal distribution weighted geometric (DLNDWG) operator, and develop a method for dynamic SMCDM with log-normally distributed random variables. This method uses the DLNDWG operator and the LNDWG operator to aggregate the log-normally distributed criterion values, utilizes the entropy model of Shannon to generate the time weight vector, and utilizes the expectation values and variances of log-normal distributions to rank the alternatives and select the best one. Finally, an example is given to illustrate the feasibility and effectiveness of this developed method.

In the title compound, C22H14ClN3, prepared by a one-pot reaction under microwave irradiation, the dihedral angles between the central pyridine ring and the pendant naphthyl and chlorobenzene ring systems are 49.2 (2) and 58.2 (3)°, respectively. In the crystal, inversion dimers linked by pairs of N—H...N hydrogen bonds generate R22(8) loops. The pyridine N atom is the acceptor.

In the title compound, C12H7Cl3N4O, the dihedral angle between the pyrazole and benzene rings is 35.6 (3)°. In the crystal, molecules are linked by N—H...O hydrogen bonds generating C(4) chains propagating in [100].

In the title compound, C13H8Cl3NO, the dihedral angle between the benzene rings is 63.2 (2)°. In the crystal, N—H...O hydrogen bonds link the molecules into C(4) chains propagating in [001]. Weak aromatic π–π stacking also occurs [centroid–centroid separations = 3.759 (3) and 3.776 (3) Å].

The title compound, C22H14FN3, was prepared by a one-pot condensation using malononitrile, an aromatic aldehyde, a methyl ketone and ammonium acetate as reactants under microwave irradiation. The pyridine ring is twisted with respect to the benzene ring and the naphthalene ring system, making dihedral angles of 41.9 (1) and 45.2 (1)°, respectively. In the crystal, molecules are connected via intermolecular N—H...N and C—H...F hydrogen bonds, forming a three-dimensional network.

In the title complex, [CdCl2(C4H8O2)]n, two different CdII ions are present, one in a general position and one with site symmetry 2. The CdII ions are coordinated by two O atoms from two 1,4-dioxane ligands and four chloride anions in a slightly distorted octahedral geometry and is connected to neighboring CdII ions by two bridging chloride anions, generating infinite linear chains along the a axis. These chains are further interconnected by bridging 1,4-dioxane ligands, affording a three-dimensional network.

In the title compound, C11H16N4O2, the dihedral angle between the benzene ring and the plane of the four carbon atoms in the piperazine ring is 12.17 (3)°; the latter ring adopts a chair conformation. An intramolecular N—H...O hydrogen bond generates an S(6) ring. In the crystal, the molecules are linked by N—H...N hydrogen bonds, forming chains.

In the title compound, C10H9N3S, the dihedral angle between the aromatic rings is 8.09 (14)°. In the crystal, a C—H...N interaction links the molecules, forming chains.

In the molecule of the title compound, C21H22N4O3, the pyrimidine ring is oriented at dihedral angles of 0.51 (3) and 50.76 (3)° to the pyridine and benzene rings, respectively. In the crystal structure, intermolecular N—H...N hydrogen bonds link the molecules into centrosymmetric dimers, forming R22(24) ring motifs; the dimers are linked by intermolecular C—H...O hydrogen bonds into a two-dimensional network. π–π contacts between the benzene rings and between the pyrimidine and pyridine rings [centroid–centroid distances = 3.891 (1) and 3.646 (1) Å, respectively] may further stabilize the structure. Two weak C—H...π interactions are also present.

In the molecule of the title compound, C16H10BrFO, the indane ring system is planar with a maximum deviation of 0.020 (3) Å. An intramolecular C—H...O interaction results in the formation of a planar ring, which is oriented at dihedral angles of 2.24 (3) and 2.34 (3)° with respect to the adjacent rings. π–π contacts between the benzene and indane rings [centroid–centroid distances = 3.699 (1) and 3.786 (1)Å] may stabilize the crystal structure.