Interval type-2 fuzzy multi-attribute decision-making approaches for evaluating the service quality of Chinese commercial banks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In today’s world, with increased competition, the service quality of Chinese commercial banks is recognized as a major factor that is responsible for enhancing competitiveness. Therefore, it is necessary to evaluate and analyse the service quality of Chinese commercial banks to realize their stable development. The service quality evaluation could be recognized as a multi-attribute decision-making (MADM) problem with multiple assessment attributes, both being of a qualitative and quantitative nature. Owing to the growing complexity and high uncertainty of the financial environment, the assessments of attributes cannot always possibly express using a real and/or type-1 fuzzy number. Additionally, a heterogeneous relationship often exists among the attributes under many real decision cases. In this study, we create two MADM approaches to handle decision-making problems with interval type-2 fuzzy numbers (IT2FNs) and offer their application to service quality evaluations of commercial banks problems. Specifically, we first define some operations on IT2FNs based on Archimedean T-norms (ATs) and develop a bi-directional projection measure of IT2FNs. Next, by combining the generalized Banzhaf index, the Choquet integral and IT2FNs, we propose the interval type-2 fuzzy Archimedean Choquet (IT2FAC) operator, the Banzhaf IT2FAC (BIT2FAC) operator and the 2-additive BIT2FAC (2ABIT2FAC) operator. Then, we establish two optimal models for deriving the weights of attributes based on a bi-directional projection measure of IT2FNs and Banzhaf function. Finally, we create two novel MADM methods under interval type-2 fuzzy contexts, where an illustrative case concerning the service quality evaluation of Chinese commercial banks is used to explain the created MADM approaches

Bis(2-{2-[2-(benzyl­carbamo­yl)phen­oxy]acetamido}­eth­yl)ammonium nitrate ethanol disolvate

In the title compound, C36H40N5O6 +·NO3 −·2C2H5OH, the nitrate anion is disordered over the two orientations of equal occupancy while the solvent mol­ecule reveals large displacement parameters. The cation is formed by protonation of the N atom of a secondary amine in the middle of the flexible chain and the whole compound has crystallographically imposed C-2 symmetry with the crystallographic b axis. An O atom of the nitrate anion links the acidic H atoms of the cation via N—H⋯O hydrogen bonding. In addition, neighbouring cations are connected by inter­molecular N—H⋯O hydrogen bonds and π–π inter­actions between the benzamide groups of the cations [centroid–centroid distance = 4.000 (3) Å], forming a chain along [001]. The ethanol solvent mol­ecules are arranged on the side of the chain through O—H⋯O hydrogen bonds

Microfluidic mass production of stabilized and stealthy liquid metal nanoparticles

Functional nanoparticles comprised of liquid metals, such as eutectic gallium indium (EGaIn) and Galinstan, present exciting opportunities in the fields of flexible electronics, sensors, catalysts, and drug delivery systems. Methods used currently for producing liquid metal nanoparticles have significant disadvantages as they rely on both bulky and expensive high-power sonication probe systems, and also generally require the use of small molecules bearing thiol groups to stabilize the nanoparticles. Herein, we describe an innovative microfluidics-enabled platform as an inexpensive, easily accessible method for the on-chip mass production of EGaIn nanoparticles with tunable size distributions in an aqueous medium. We also report a novel nanoparticle-stabilization approach using brushed polyethylene glycol chains with trithiocarbonate end-groups negating the requirements for thiol additives whilst imparting a ‘stealth’ surface layer. Furthermore, we demonstrate a surface modification of the nanoparticles using galvanic replacement, and conjugation with antibodies. We envision that the demonstrated microfluidic technique can be used as an economic and versatile platform for the rapid production of liquid metal-based nanoparticles for a range of biomedical applications.

Comparison of Apparent Diffusion Coefficient and T2 Relaxation Time Variation Patterns in Assessment of Age and Disc Level Related Intervertebral Disc Changes

Purpose To compare the variation patterns of ADC and T2 values in different age and intervertebral disc (IVD) levels, thus to identify their sensitivities in assessing age and disc level related IVDs changes. Materials and Methods The T2 and ADC values were recorded from 345 IVDs of 69 volunteers. Kendall's correlation analysis was used to identify the relationship between age and T2/ADC mean values respectively. The one-way analysis of variance (ANOVA) with post hoc analysis was then applied to test the differences of T2 and ADC values among different IVD levels and age groups, followed by linear regression analysis between age (45 years) and T2/ADC mean values. This study was approved by the Ethics Committee of the Chinese Academy of Medical Sciences and the Peking Union Medical College Hospital. Results: Significant negative correlation was observed between age and T2/ADC mean values. The T2 and ADC values showed significant differences among IVD levels and among age groups except for T2 values in age group 1 (25–34 years) and group 2 (35–44 years), and for ADC values at L1–2 level. Both T2 and ADC values showed significant differences between young (age45 years) at each IVD level. A linear relationship was observed between age and T2/ADC mean values in the elderly group as well as in the young group for the ADC mean values, while no such tendency was identified in the young group for the T2 mean values. Conclusions: ADC values may be a more sensitive parameter than T2 in assessing age and disc level related intervertebral disc changes

Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers

Evolving intelligent systems (EISs), particularly, the zero-order ones have demonstrated strong performance on many real-world problems concerning data stream classification, while offering high model transparency and interpretability thanks to their prototype-based nature. Zero-order EISs typically learn prototypes by clustering streaming data online in a “one pass” manner for greater computation efficiency. However, such identified prototypes often lack optimality, resulting in less precise classification boundaries, thereby hindering the potential classification performance of the systems. To address this issue, a commonly adopted strategy is to minimise the training error of the models on historical training data or alternatively, to iteratively minimise the intra-cluster variance of the clusters obtained via online data partitioning. This recognises the fact that the ultimate classification performance of zero-order EISs is driven by the positions of prototypes in the data space. Yet, simply minimising the training error may potentially lead to overfitting, whilst minimising the intra-cluster variance does not necessarily ensure the optimised prototype-based models to attain improved classification outcomes. To achieve better classification performance whilst avoiding overfitting for zero-order EISs, this paper presents a novel multi-objective optimisation approach, enabling EISs to obtain optimal prototypes via involving these two disparate but complementary strategies simultaneously. Five decision-making schemes are introduced for selecting a suitable solution to deploy from the final non-dominated set of the resulting optimised models. Systematic experimental studies are carried out to demonstrate the effectiveness of the proposed optimisation approach in improving the classification performance of zero-order EISs

Functional Liquid Metal Nanoparticles Produced by Liquid-Based Nebulization

Functional liquid metal nanoparticles (NPs), produced from eutectic alloys of gallium, promise new horizons in the fields of sensors, microfluidics, flexible electronics, catalysis, and biomedicine. Here, the development of a vapor cavity generating ultrasonic platform for nebulizing liquid metal within aqueous media for the one-step production of stable and functional liquid metal NPs is shown. The size distribution of the NPs is fully characterized and it is demonstrated that various macro and small molecules can also be grafted onto these liquid metal NPs during the liquid-based nebulization process. The cytotoxicity of the NPs grafted with different molecules is further explored. Moreover, it is shown that it is possible to control the thickness of the oxide layer on the produced NPs using electrochemistry that can be embedded within the platform. It is envisaged that this platform can be adapted as a cost-effective and versatile device for the rapid production of functional liquid metal NPs for future liquid metal-based optical, electronic, catalytic, and biomedical applications