Modeling target group heterogeneity in experimental consumer studies

Acceptance of a product by a consumer may result from a convoluted interplay between product attributes and individual characteristics of that consumer. Different methods that systematically combine product properties with consumer groups segmented on such characteristics have provided unprecedented insight, but ignore heterogeneity in acceptance within each consumer group. Although such knowledge is invaluable for targeted marketing, dedicated methods for consumer group heterogeneity are lacking. The authors aim to fill this gap by the Individual Differences (InD) method, which models differences between consumers within the same target group. The method scores the ‘diffusion’ within each group, shows how much each consumer contributes to that, and relates this information to product properties. Thereby also novel groups may be discovered, with attributes not covered in the consumer segmentation. The illustrative consumer study on apple juice reveals how young women differ in their price-consciousness and their acceptance on specific preparation technologies more than older women. Although men exhibit heterogeneity on the same product attributes, their mutual variability is considerably lower and they thereby form more homogeneous target groups.     

Trust based consensus model for social network in an incomplete linguistic information context

A theoretical framework to consensus building within a networked social group is put forward. This article investigates a trust based estimation and aggregation methods as part of a visual consensus model for multiple criteria group decision making with incomplete linguistic information. A novel trust propagation method is proposed to derive trust relationship from an incomplete connected trust network and the trust score induced order weighted averaging operator is presented to aggregate the orthopairs of trust/distrust values obtained from different trust paths. Then, the concept of relative trust score is defined, whose use is twofold: (1) to estimate the unknown preference values and (2) as a reliable source to determine experts’ weights. A visual feedback process is developed to provide experts with graphical representations of their consensus status within the group as well as to identify the alternatives and preference values that should be reconsidered for changing in the subsequent consensus round. The feedback process also includes a recommendation mechanism to provide advice to those experts that are identified as contributing less to consensus on how to change their identified preference values. It is proved that the implementation of the visual feedback mechanism guarantees the convergence of the consensus reaching process.     

Styrenated urethane oil synthesis via CuAAC “click” chemistry approach

In this study, a novel route for the modification of sunflower oil-based partial triglycerides with styrene (St) was described. For this purpose, in the first step, copolymers of St and 4-chloromethyl styrene (P(St-co-CMS)) were synthesized by free radical polymerization (FRP) and controlled/living radical polymerization (nitroxide mediated radical polymerization (NMRP)) methods. In the second step, chloro groups of these samples were transformed into azido groups by using NaN₃/DMF and then azido groups were coupled with propargyl alcohol to achieve hydroxyl functional polystyrene chain (PSt-OH) via Cu(I)-catalyzed 1,3-dipolar azide-alkyne cycloaddition (CuAAC) “click” chemistry approach. Finally, alcohol groups of PSt-OH and the partial glyceride (PG) were combined by the reaction with toluene 2,4-diisocyanate (TDI). As a result, styrenated urethane oil (PG-TDI-PSt) was obtained as an oil-based binder. The structures were determined by FT-IR, ¹H NMR and GPC analyses, and film properties of the products were examined according to the related standards. (PG-TDI-PSt) gave good film properties, and therefore could be considered as an applicable oil-based binder.     

One-Pot Methods for the Protection and Assembly of Sugars

In recent years, there has been rapid expansion of glycan synthesis, fueled by the recognition that the structural complexity of sugars translates to a myriad of biological functions. Such chemical syntheses involve many challenges, mostly due to the regio- and stereochemical aspects of glycosidic bond formation. One-pot strategies were developed to assist in attaining faster and more economical access to the glycan constructs. In this front, achievements in protecting group manipulation, glycosylation, and combinations of these have been reported. Protecting group manipulations in one pot take advantage of the reaction compatibility of commonly used transformations, many of which occur in high regioselectivity. Sequential glycosylations, on the other hand, rely on leaving group orthogonalities and reactivity tuning, as well as the preactivation technique. Altogether, these approaches offer attractive means to the much needed glycan structures and, consequently, help usher in advances in glycoscience.     

Forgotten monomers: isotactic polymers from N‐benzyl‐3‐methylenepyrrolidin‐2‐one via free radical polymerization

N‐Benzyl‐3‐methylenepyrrolidin‐2‐one ( 3 ) was synthesized and homopolymerized under free radical conditions. The configurational microstructure of poly(N‐benzyl‐3‐methylenepyrrolidin‐2‐one) ( 4 ) is isotactic with a minor tendency to syndiotacticity. Monomer 3 was also homopolymerized in water in the presence of methylated β‐cyclodextrin. The glass transition temperature of 4 of 124 °C was compared with the lower value of 61 °C of the ring‐opened analogue poly(N‐benzyl‐N‐ethylacrylamide). © 2015 Society of Chemical Industry     

Minimum cost consensus model for CRP-driven preference optimization analysis in large-scale group decision making using Louvain algorithm

Large-scale group decision-making problems based on social network analysis and minimum cost consensus models (MCCMs) have recently attracted considerable attention. However, few studies have combined them to form a complete decision-making system. Accordingly, we define the satisfaction index to optimize the classical MCCM by considering the effect of the group on individuals. Similarly, we define the consistency index to optimize the consensus reaching process (CRP). Regarding the evolution of the consensus network, the Louvain algorithm is used to divide the entire group into several subgroups to ensure that each subgroup is independent but has strong cohesion. By constructing the MCCM based on the satisfaction index and the optimized consensus-reaching process, the group opinions in each subgroup are ranked to obtain the final ranking of alternatives. Finally, to verify the validity of CRP and the practical value of the proposed model, we conduct consensus network evolution and decision-making analysis in the case of a negotiation between the government and polluting companies to achieve uniform pollution emissions. Sensitivity analysis is performed to demonstrate the stability of the subgroup weights. Furthermore, a comparative analysis using existing models verifies the effectiveness of the proposed model.     

后处理对爆轰纳米金刚石表面官能团的影响

分别在高锰酸钾与浓硫酸的混合溶液、空气、氢气、真空以及氩气中对爆轰纳米金刚石进行后处理,研究了后处理方法对其表面官能团的影响。采用X射线衍射仪、高分辨透射电子显微镜、傅立叶变换红外光谱仪和差示扫描量热仪对后处理前后纳米金刚石的微观结构、性能和表面状态进行了研究。结果表明:纳米金刚石颗粒形状为球形或椭球形,平均粒径约为5 nm,在空气中的起始氧化温度约为550 ℃,在氢气、真空和氩气中的石墨化温度分别约为284 ℃、1 146 ℃和1 184 ℃。纳米金刚石在后处理前表面含有大量的官能团,如-OH、-CH₃、-CH₂、CO₂、-C==O、-COOH和-C-O-C等。在氢气中对纳米金刚石进行处理,可使部分官能团从表面解吸而由氢取代,悬键与氢结合可有效防止二次吸附,是去除爆轰纳米金刚石表面官能团的低成本、高效方法。     

Alkali-doped hyperbranched cross-linked polybenzimidazoles containing benzyltrimethyl ammoniums with improved ionic conductivity as alkaline direct methanol fuel cell membranes

Development of anion exchange membranes (AEMs) with good performance, such as high conductivity, good alkaline stability and mechanical strength, has been a hot topic for the fuel cell application. Here, a novel kind of hyperbranched cross-linker decorated with quaternary ammonium groups was introduced to polybenzimidazole (PBI) membranes and QOPBI-x membranes (where x is the weight ratio of the hyperbranched cross-linker). Compared with the linear OPBI membrane (0.091 S cm⁻¹), QOPBI-x membranes displayed an improved ionic conductivity (up to 0.122 S cm⁻¹) at 60°C after they were doped in 6 M KOH for 7 days. The KOH-doped QOPBI-x membranes also exhibited a high tensile strength (54.5-61.7 MPa) and superior alkaline stability. There is almost no decline in the ionic conductivity after being immersed in a 6 M KOH solution for 30 days. In addition, the alkaline direct methanol fuel cell (ADMFC) performance based on the KOH-doped OPBI and QOPBI-x membranes is described. The QOPBI-15 membrane displayed good performance (75.6 mW cm⁻²), which is 33.3% higher than the OPBI membrane (56.7 mW cm⁻²).     

Enhanced electrocatalytic performance of Cu0.02S0.01/rGO hybrid for oxygen reduction reaction in alkaline medium at low temperature

Graphene, is a carbon allotrope, which is widely used as a substrate for various catalysts due to its interesting physicochemical properties. In the present study, graphene oxide sheets were prepared from graphite, then, the graphene oxide surface was modified by a low-temperature method using sulfur and copper atoms to obtain pseudo-enzyme Cu/S/Graphene prosthetic group. The current density passing through Cu/S/Graphene catalyst was four times higher than that passing through graphite. The novel copper-based catalyst had an extraordinary performance for oxygen reduction reaction (ORR) due to the unique bio-inspired and stoichiometric structure. The results of Raman and Dispersive X-ray spectroscopy confirmed the presence of ultra-low content of copper (2%) and sulfur (1%) atoms on the graphene surface. Thermogravimetric analysis indicated a strong interaction between nanoparticles and graphene layers. The number of electrons transferred for ORR varied from 3.98 to 4.16 in a wide range of over-potentials indicating an effective 4-electron pathway form O₂ to H₂O. The Tafel slopes indicated insignificant amount of formed copper oxide on the catalyst surface. The catalyst showed excellent electrochemical durability and its half-wave potential (E_1/2) was exhibited a negative shift only 8.2 mV after 10000 cycles.     

Some q-rung orthopair uncertain linguistic aggregation operators and their application to multiple attribute group decision making

q-Rung orthopair fuzzy sets (q-ROFSs), originally presented by Yager, are a powerful fuzzy information representation model, which generalize the classical intuitionistic fuzzy sets and Pythagorean fuzzy sets and provide more freedom and choice for decision makers (DMs) by allowing the sum of the $q\mathrm{t}\mathrm{h}$ power of the membership and the $q\mathrm{t}\mathrm{h}$ power of the nonmembership to be less than or equal to 1. In this paper, a new class of fuzzy sets called q-rung orthopair uncertain linguistic sets (q-ROULSs) based on the q-ROFSs and uncertain linguistic variables (ULVs) is proposed, and this can describe the qualitative assessment of DMs and provide them more freedom in reflecting their belief about allowable membership grades. On the basis of the proposed operational rules and comparison method of q-ROULSs, several q-rung orthopair uncertain linguistic aggregation operators are developed, including the q-rung orthopair uncertain linguistic weighted arithmetic average operator, the q-rung orthopair uncertain linguistic ordered weighted average operator, the q-rung orthopair uncertain linguistic hybrid weighted average operator, the q-rung orthopair uncertain linguistic weighted geometric average operator, the q-rung orthopair uncertain linguistic ordered weighted geometric operator, and the q-rung orthopair uncertain linguistic hybrid weighted geometric operator. Then, some desirable properties and special cases of these new operators are also investigated and studied, in particular, some existing intuitionistic fuzzy aggregation operators and Pythagorean fuzzy aggregation operators are proved to be special cases of these new operators. Furthermore, based on these proposed operators, we develop an approach to solve the multiple attribute group decision making problems, in which the evaluation information is expressed as q-rung orthopair ULVs. Finally, we provide several examples to illustrate the specific decision-making steps and explain the validity and feasibility of two methods by comparing with other methods.