Inherent Characteristics Research Articles

Robust multi-stage progressive autoencoder for hyperspectral anomaly detection

Recently, Autoencoders (AEs) have demonstrated remarkable performance in the field of hyperspectral anomaly detection, owing to their powerful capability in handling high-dimensional data. However, they often overlook the inherent global distribution characteristics and long-range dependencies in hyperspectral images (HSI). This oversight makes it challenging to accurately characterize and describe boundaries between different backgrounds and anomalies in complex HSI, thereby affecting detection accuracy. To address this issue, a robust multi-stage progressive autoencoder for hyperspectral anomaly detection (RMSAD) is proposed. Initially, a progressive multi-stage learning framework based on convolutional autoencoders is employed. This framework incrementally reveals and integrates deep contextual features along with their long-range dependencies in HSI, aiming to accurately characterize the background and anomalies. Subsequently, an innovative multi-scale fusion strategy is introduced at the intersections of each stage, reinforcing the learning and representation of background and global spatial details across multiple stages. Finally, by collectively extracting abnormal spatial information across stages, effectively reducing the tendency of autoencoders to reconstruct anomalies. This ensures the efficient restoration and replication of global textural details in HSI. The experimental results on the six HSI datasets demonstrate that the proposed RMSAD is superior to other state-of-the-art methods.

[o-C2B10H10]3 as a trimer aggregate of spherical aromatic carboranes. Persistence and interplay between spherical aromatic states

Envisaging cluster-based materials requires a fundamental understanding of the aggregation processes and resulting properties. The inherent spherical aromatic properties of carboranes trigger further evaluation of the persistence of such property in the resulting cluster aggregate. Here, we evaluated the formation of a trimeric species based on the neutral [o-C2B10H12] cluster on the [o-C2B10H10]3 form. The obtained results show that the inherent spherical aromatic characteristics of the constituent building units remain in the resulting trimer aggregate as three spherical aromatic states. Thus, cluster-based materials can be envisaged from stable spherical aromatic units, guiding further experimental realization of cluster-based aggregates.

Why active Willis metamaterials? A controllability and observability perspective

Recently, active Willis metamaterials (AWM) have been the focus of extensive investigations because of their unique electro-elastic coupling characteristics. However, the treatments of this class of materials have been carried out exclusively, in all the available literature, by approaches that do not rely on solid control theory basis. In this paper, the emphasis is placed on revealing very important control features that are inherent to this class of materials because of their Willis coupling characteristics. These features lie in the enhanced controllability and observability properties of the AWM as compared to non-Willis active materials. Such control properties enable the AWM to possess broad sensing and actuation capabilities that can lend this material to be an effective means for monitoring and controlling the behavior of numerous critical applications, such as acoustic cloaking, particularly when integrated with appropriate robust control strategies. A simple example of a piezoelectric-based AWM is presented to demonstrate its effective control capabilities and distinguish this class of materials from conventional materials. In the selected example, the AWM is structured from two dissimilar masses connected by a piezoelectric spring. Lagrange dynamics formulation is utilized to generate the equations governing the Willis coupling, the piezoelectric coupling, and reveal the inherent control features. With this developed controlled-based structure of the AWM, it is shown that the AWM can simultaneously monitor and control both the strain and velocity whereas the conventional active material, which is formed from two similar masses connected by a piezoelectric spring, can only measure and control the strain alone. It is envisioned that the revealed control metrics for the simple one-dimensional AMW example can serve as means for investigating the potential of AMW's of higher dimensionality.

High-resolution NMR spectroscopic approaches to quantify PET microplastics pollution in environmental freshwater samples

Reliable identification and precise quantification of microplastics pollution of the environment are essential prerequisites to comprehend the impact of microplastics on Earth’s ecosystems. In this study, we propose a workflow to examine polyethylene terephthalate (PET) contamination of environmental surface waters by applying high-resolution nuclear magnetic resonance (NMR) spectroscopic approaches. The detection of PET by high-resolution NMR spectroscopy enables the unambiguous identification and - at the same time - precise quantification at atomic resolution independent from the size of the particles obtained from surface waters. Monitoring the properties of translational diffusion and relaxation of PET chains present in the samples obtained from Lake Constance water by filtration (‘Manta trawls’), extraction and dissolving, hints towards a rather heterogeneous distribution in length of the PET chains. The workflow developed here achieved a limit of detection of 192.2 ng PET and a recovery rate of 88 ± 25% for PET microplastics that was spiked to the Manta trawls. The NMR driven analysis led to a concentration determination of 335 ± 200 ng PET per cubic meter of Lake Constance water. The workflow developed here offers not only a simple and reliable quantitative determination of the mass of PET in environmental samples independent of particle size but is additionally providing insights into the inherent polymeric features of PET, which are not accessible through other established methods of microplastics detection. Therefore, a broad application of the NMR spectroscopic approach presented here can be assumed.

Swelling problems in immobilized filler: an improvement method and comparative study of the effect of different fillers on biotrickling filters.

Immobilized fillers have been increasingly utilized in biotrickling filters (BTFs) due to their positive impact on shock load resistance and recovery performance. However, due to the inherent characteristics of its immobilized carrier, the immobilized filler is prone to swelling during the long-term operation of the system, resulting in increased pressure drop. Polyurethane (PU) sponge was used as the cross-linked skeleton of immobilized filler and compared with direct emulsified cross-linked immobilized filler for treating ethylbenzene gas. In the early stage, both fillers can maintain good performance despite changes in the inlet concentration and short-term stagnation. However, on the 107th day of operation, the immobilized filler experienced swelling, and the pressure drop sharply increased to 137.2 Pa, while the PU immobilized filler was still able to maintain a low-pressure drop level. The results of the microbial diversity analysis revealed that the microbial community structure of PU immobilized fillers remained relatively stable when responding to the fluctuations in operating conditions. PU sponges as the skeleton can effectively prolong the service life of the immobilized filler and improve the performance of the biotrickling filter.

The Financial Inclusion Question in Zimbabwe’s Post-COVID -19, New Normal: Implications for Adoption of Financial Technology (FinTech) on Service Providers

Financial inclusion will be accelerated by the technological opportunities for online financial transactions brought forth by the COVID-19 outbreak. As a result, because there were fewer digital financial transactions, the threats to COVID-19 that were present previously are now more substantial. The aim of this article is to assess the dangers, challenges, and opportunities for financial inclusion brought forth by the use of technology by COVID-19. According to the article, the inherent characteristics of financial technology (FinTech) in connection to financial inclusion allow it to reduce the negative economic and social effects of the ongoing COVID-19 situation. Under COVID-19, the introduction of digital financial transactions has sped up corporate operations and cut expense on doing business. As a result, women now have greater access to transactions involving financial technology (FinTech). The growth of digital financial transactions has made contactless and cashless purchases possible throughout the COVID-19 crisis. The expansion of digital financial inclusion makes it easier to swiftly and effectively implement public assistance programs, such as those for epidemic-affected women. Financial inclusion is being boosted by digital finance, which may eventually replace or improve traditional banking institutions. Working from home has undergone a "revolution" in a number of industries during COVID-19, including banking. Businesses should identify the optimal operating model mix for the future and make sure they have the infrastructure to support widespread, mass flexible working. This calls for reevaluating the function and application of corporate real estate. Since the labor force is likely to become more automated at the same time, resilience is essential. Conceptual Framework of this study is based on the financial inclusion and FinTech concepts which are the main variables guiding the study and it is underpinned by the theories of diffusion of innovation and the Financial Intermediation.

[Translated article] Approach and management of patients injured by bullfighting trauma

Introduction: Bullfighting festivals are attributed to the cultural idiosyncrasies of the Ibero-American people, posing an extreme risk to the physical integrity of the participants. Spain is considered the country with the highest number of bull-related celebrations worldwide and, therefore, with the highest number of patients injured by bullfighting trauma treated, thus justifying a public health problem. The generalities associated with this type of trauma define the people injured as polytraumatised patients. In addition, it is important to know the kinematics of the injuries and their specific characteristics, in order to implement quality medical-surgical care.Methods: scientific review of the literature to promote a comprehensive guide for the medical-surgical management of patients injured by bullfighting trauma.Results: We described the guidelines to standardise protocols for in-hospital approach of patients injured by bullfighting trauma.Conclusions: Bullfighting trauma is considered a real health problem in the emergency departments of the ibero-Americans countries, especially in Spain, where bullfighting is part of the national culture. The inherent characteristics of these animals cause injuries with special aspects, so it is important to know the generalities of bullfighting trauma. Because of the multidisciplinary approach, these guidelines are adressed to all healthcare providers involved in the management of these patients. It is essential to establish particular initial care for this type of injury, specific therapeutic action and follow-up based on the medical-surgical management of the trauma patient in order to reduce the associated morbidity and mortality.

Optimization of Energy Compensation Layered Structure of Geiger- Müller Counters

The dose rate measured by Geiger-Müller (GM) detectors plays a crucial role in assessing radiation fields. Due to the inherent characteristics of GM tubes, the energy response is inconsistent across different types or energies of radiation, leading to significant discrepancies in dose rates for radiation of the same intensity. This paper addresses the energy response differences of GM tubes and improves the spatial design of the compensation structure based on traditional shielding compensation methods. Incorporating a multi-layer compensation material model improved the uniformity of energy response across different energy levels. Monte Carlo simulations validated that the designed compensation model effectively enhances the accuracy of GM tube measurements. Initially, a perforated design was used, which improved the relative energy response by three times compared to the traditional segmented compensation method. Additionally, after applying layered compensation optimization to the lead shielding model with the perforated design, the compensation effect was further increased by 20.3%. The final root mean square error (RMSE) of 0.429 indicates that the improved energy compensation method significantly enhances the measurement performance of GM detectors, providing more design models and optimization directions for improving the energy response of dosimeters.

Pre-syntactic impoverishment: Premature exponence in Harmonic Serialism

Impoverishment is a feature deletion operation that is standardly taken to require a post-syntactic approach to inflectional morphology (like, in particular, Distributed Morphology, as in Halle & Marantz 1993 ). Given that by now a lot of empirical evidence in support of such an operation has been accumulated, impoverishment can be viewed as a good argument in favour of the post-syntactic approach, given a Chomskyan Y-model of grammar in which inflectional morphology is considered an autonomous component of grammar (i.e., not subsumed under syntax proper). Against this background, the main goal of the present contribution is to show that a pre-syntactic approach to impoverishment becomes available if the complete well-formed sets of morpho-syntactic features that are required in any non-syntactic realizational approach to inflectional morphology (cf. Stump 2001 ; Inkelas 2016 ) are not given a declarative characterization (as is normally assumed), but arise incrementally, by iterated addition of features. On this view, pre-syntactic impoverishment is actually premature exponence brought about by late addition of context features, and the interaction between impoverishment and morphological exponence is not one of bleeding (as in post-syntactic approaches) but one of counter-feeding. The new concept of impoverishment is implemented in a pre-syntactic model of inflectional morphology developed in Müller (2020) , which is based on Harmonic Serialism, a derivational version of Optimality Theory (cf. Prince & Smolensky 2004 ). Finally, while pre-syntactic impoverishment is basically a mirror image of post-syntactic impoverishment, it turns out to be more restrictive since it ceteris paribus predicts that there is no impoverishment of inherent features: Features that are not added cannot be added late. I suggest that this prediction is confirmed by evidence from gender features and inflection class features.

Beyond the myth: understanding women's impulsive retail footwear shopping

PurposeThis research focuses on common misconceptions about the factors driving women to purchase footwear impulsively. Its primary objective is to explore how emotional and social triggers specifically influence women's purchasing decisions, contrasting with the traditionally rational consumer models.Design/methodology/approachAn online questionnaire was administered to a sample of women, yielding 199 useable responses.FindingsThe findings reveal the key determinants of women's impulsive retail footwear purchases, which include self-regulation, hedonic motivations and the influence of the retail store environment. This research challenges the prevailing assumption that women's passion for shopping is driven solely by inherent characteristics and suggests that external factors substantially shape their impulsive buying behaviour. In summary, the stereotypical portrayal of women as compulsive retail footwear shoppers may result more from external stimuli and environmental factors rather than an intrinsic trait.Originality/valueThis study improves the existing knowledge of women’s impulsive buying behaviour by unveiling the determinants of women's impulsive footwear purchases and assessing whether prevailing stereotypes hold true.

A three-phase framework for mapping barriers to blockchain adoption in sustainable supply chain

PurposeBlockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.Design/methodology/approachA three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.FindingsThe findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.Practical implicationsThe outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.Originality/valueThe research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.

Multilevel Stimuli-Responsive Smart "Sandwich" Label with Physical Unclonable Functions Bionic Wrinkles and Space-Selective Fluorescence Patterns.

With the increasing popularity of the internet, it brings convenience to lives while also increases security risks. Physical Unclonable Functions (PUFs) can generate random, unclonable, and unique identifiers using their inherent physical characteristics, which have broad prospects in anti-counterfeiting. Herein, inspired by the irregular tree bark fissures and random skin wrinkles found in nature, a method for creating complex micro-wrinkles with unclonable random patterns is proposed by simply stretching hydrogels. The random texture information contained in the micro-wrinkles is digitized into binary codes using an adaptive threshold algorithm. Additionally, a novel "sandwich" label with a multilevel intelligent anti-counterfeiting system is proposed. The first-level involves photoluminescence encryption with adjustable luminescence within visible light range and modulated luminescence at different excitation wavelengths; the second-level includes strain-related mechanical encryption, and the third-level consists of highly random and unclonable micro-wrinkles. The certification difficulty increases as the anti-counterfeiting grade increases, thereby enhancing label security. Furthermore, space-selective doping of rare earth metal-organic framework (RE-MOF) fluorescent materials in hydrogels is achieved through the use of screen-printing technology. The concept of novel multilevel smart anti-counterfeiting PUF labels will further enhance current levels of counterfeiting prevention.

Connection-Aware Digital Twin for Mobile Adhoc Networks in the 5G Era

5G Mobile Adhoc Networks (5G-MANETs) are a popular and agile solution for data transmission in local contexts while maintaining communication with remote entities via 5G. These characteristics have established 5G-MANETs as versatile communication infrastructures for deploying contextual applications, leveraging physical proximity while exploiting the possibilities of the Internet. As a result, there is growing interest in exploring the potential of these networks and their performance in real-world scenarios. However, the management and monitoring of 5G-MANETs are challenging due to their inherent characteristics, such as highly variable topology, unstable connections, energy consumption of individual devices, message routing, and occasional inability to connect to 5G. Considering these challenges, the proposed work aims to address real-time monitoring of 5G-MANETs using a connection-aware Digital Twin (DT). The approach provides two main functions: offering a live virtual representation of the network, even in scenarios where multiple nodes lack 5G connectivity, and estimating the performance of the infrastructure, enabling the specification of customized conditions. To achieve this, a communication architecture is proposed, analyzing its components and defining the involved processes. The DT is implemented and evaluated in a laboratory setting, assessing its accuracy in representing the physical network under varying conditions of topology and Internet availability. The results show 100% accuracy for the DT in fully connected topologies, with ultra-low latency averaging under 80 ms, and suitable performance in partially connected contexts, with latency averages below 3000 ms.

Identification and characterization of alkaline hydrolytic degradation products of ivacaftor by UPLC-PDA and UPLC-ESI-QTOF-MS techniques.

The study of inherent stability characteristics of drugs has been advocated to be important by various regulatory agencies like the ICH, USFDA, and others. The current work was envisaged to investigate the forced degradation profile of the drug ivacaftor under ICH-prescribed stress conditions, identification of its potential degradants, and postulation of the degradation routes for their generation. The stress degradation studies were performed on the drug as per the ICH guideline Q1A(R2). A UPLC-photodiode array-based chromatographic method was developed to satisfactorily resolve the drug from its degradation products, validated in accordance with various ICH prescribed parameters, and assessed for its BAGI practicality index. The degradation products were identified and characterized by UPLC-ESI-QTOF-MS studies. The drug was found to significantly degrade under conditions of alkaline hydrolytic stress and it was found to be stable under all other stressor environments including acid/neutral hydrolytic, photolytic, thermal, and oxidative stress. Four alkaline hydrolytic degradation products (I-IV) were revealed by UPLC-QTOF-MS studies which were well-resolved from the drug over a C18 UPLC column by the developed UPLC-PDA method. The detection wavelength was selected as 310 nm. Characterization of the four degradation products (I-IV) was carried out by their mass spectral data and their respective degradation routes were elucidated. A UPLC-PDA method was developed and validated for ivacaftor and its practicality BAGI index was computed. Four alkaline hydrolytic degradation products of ivacaftor were revealed through UPLC-ESI-QTOF-MS studies and corresponding degradation routes were elucidated.

NAVIGATING THE REGULATORY LANDSCAPE OF VOLUNTARY SUSTAINABILITY STANDARDS IN INTERNATIONAL FOOD TRADE: A MULTILATERAL INTERPLAY - DOI: 10.12818/P.0304-2340.2024v85p171

Voluntary sustainability standards (VSSs) are non-mandatory criteria designed to foster sustainable practices throughout the global supply chain. These standards are particularly prevalent in the agri-food sector, where they aim to support wider public policy objectives such as sustainable food production, animal welfare, healthy lifestyle, and labour conditions. Significant challenges arises from the fact that VSSs, despite their voluntary nature, they often impose mandatory effect in the global supply chain. They also often lack easily-identifiable features of the product themselves. These creates systematic problems for the global food trade system, where conventional regulation address governmental measures on goods with specific inherent characteristics that can be clearly identified in the final product. This article explored the interrelationship among private VSSs, national regulations and international treaties within the agri-food industry. It highlights ambiguity surrounding the regulatory framework for VSSs under the WTO law, noting the absence of a consensus on how relevant provisions should be interpreted. Despite the diversity among various VSSs, VSSs, this article argues for the potential for harmonization and equivalence among VSSs. By aligning various VSSs and with technical regulations, it is possible to strike a balance between trade liberalization and promotion of sustainable practices.

Electric Demulsification Membrane Technology for Confined Separation of Oil-Water Emulsions.

Demulsification technology for separation of oil-water (O/W) emulsions, especially those stabilized by surfactants, is urgently needed yet remains highly challenging due to their inherent stability characteristics. Electrocoalescence has emerged as a promising solution owing to its simplicity, efficacy, and versatility, yet hindered by substantial energy consumption (e.g., >50 kWh/m3) along with undesirable Faradic reactions. Herein, we propose an innovative electric demulsification technology that leverages conductive membrane microchannels to confine oil droplets from the oil-water emulsion for achieving high energy-efficient coalescence of oil droplets. The proposed system reduces the required voltage down to 12 V, 2 orders of magnitude lower than that of conventional electrocoalescence systems, while achieving a similar separation efficacy of 91.4 ± 3.0% at a low energy consumption (3 kWh/m3) and an ultrahigh permeability >3000 L/(m2·h·bar). In situ fluorescence microscopy combined with COMSOL simulations provided insight into the fundamental mechanistic steps of an electric demulsification process confined to membrane microchannels: (1) rapid electric-field redistribution of oil droplet surfactant molecules, (2) enhanced collision probability due to confined oil droplet concentration under dielectrophoretic forces, and (3) increased collision efficacy facilitated by the membrane pore structure. This strategy may revolutionize the next generation of demulsification and oil-water separation innovations.

Multifunctional highly conductive cellulose nanopaper with ordered PEDOT:PSS alignment enabled by external surface area-promoted phase separation

Integrating cellulose, the most abundant biopolymer on Earth, with PEDOT:PSS, the most commercially available conducting polymer, can create multifunctional conductive nanopapers for sustainable electronics. However, conventional PEDOT:PSS/cellulose composites often exhibit limited conductivity, primarily due to the random distribution of PEDOT and the aggregation of PSS within the cellulose matrix. Herein, we introduce a confined phase separation approach that leverages the inherent physical characteristics of the cellulose substrate to enhance the performance of these composites. By systematically investigating the influence of the external surface area of nanocellulose on PEDOT:PSS coverage and composition evolution, we demonstrate that a higher external surface area ensures uniform PEDOT:PSS coating on nanocellulose networks and facilitates effective PSS removal during secondary doping. This process enhances phase separation and promotes ordered alignment of PEDOT chains along nanocellulose, resulting in an electrical conductivity of up to 252 S cm−1. Such highly conductive nanopapers exhibit exceptional performances in supercapacitors and electromagnetic shielding, achieving an ultrahigh specific electromagnetic shielding effectiveness of 33,122 dB cm2 g⁻1 at only 6 μm thickness. Our study highlights the critical role of cellulose substrate selection at the nanoscale and elucidates the interactions within conducting polymers, offering a promising pathway for developing high-performance, sustainable electronics.

In situ atomic observations of aggregation growth and evolution of penta-twinned gold nanocrystals

The twin boundaries and inherent lattice strain of five-fold twin (5-FT) structures offer a promising and innovative approach to tune nanocrystal configurations and properties, enriching nanomaterial performance. However, a comprehensive understanding of the nonclassical growth models governing 5-FT nanocrystals remains elusive, largely due to the constraints of their small thermodynamically stable size and complex twin configurations. Here, we conducted in situ investigations to elucidate the atomic-scale mechanisms driving size-dependent and twin configuration-related aggregation phenomena between 5-FT and other nanoparticles at the atomic scale. Our results reveal that surface diffusion significantly shapes the morphology of aggregated nanoparticles, promoting the symmetrical formation of 5-FT, especially in smaller nanoparticles. Moreover, the inherent structural characteristics of 5-FT mitigate the dominance of surface diffusion in its morphological evolution, retarding the aggregation evolution process and fostering intricate twin structures. These findings contribute to advancing our capacity to manipulate the configuration of twinned particles, enabling more predictable synthesis of functional nanomaterials for advanced engineering applications.

From the Perspective of Media Convergence: The Integration and Reference of Network Drama to Other Audio-visual Art Forms

Abstract: In recent years, the convergence of content and form between different media has become a significant trend. Online dramas, as an emerging media form based on streaming platforms, have developed rapidly since their inception, greatly impacting the market landscape of television dramas and films. Due to the inherent characteristics of streaming platforms, online dramas feature high market segmentation and expansive creative space. Many works have explored various content and form integrations, incorporating elements from other audiovisual art forms and reconstructing traditional television drama formats. Notably, the influences of films, short videos, and games on the shape of online dramas are most pronounced, demonstrating profound media convergence.

Data driven cost-sensitive boosted tree for interpretable banking systemic risk prediction

Systemic risk (SR) in the banking sector poses a significant threat to both the financial system and the real economy. Its inherent characteristics of nonlinearity, non-equilibrium, and interconnectedness make it challenging to analyze using conventional statistical methods. In this paper, a cost-sensitive gradient boosting tree algorithm, FLXGBoost, is proposed for predicting SR. FLXGBoost considers the boosted tree, XGBoost as the base framework, boosting trees as the fundamental framework, guaranteeing the robustness of SR prediction. Additionally, to tackle the challenge of extreme data imbalance prevalent in SR prediction tasks, a cost-aware loss function, focal loss, is embedded into the boosted tree to enable FLXGBoost a risk-aware fashion. Moreover, a tree-derived interpretable algorithm SHAP is incorporated into this cost-sensitive solution, making FLXGBoost an accurate and interpretable risk-aware model. Experimental results on a financial risk prediction dataset pertaining to banking SR evince the capacity of FLXGBoost to significantly reduce the misclassification rate of risk banks, thereby mitigating substantial losses attributed to erroneous predictions of risky scenarios. Moreover, compared with classical imbalanced machine learning-based SR prediction approaches, the diverse evaluation metrics of FLXGBoost show that it is a competitive solution for accurate SR prediction. Besides, the explanatory analysis further demonstrates that FLXGBoost is a promising solution to address the issue of biased predictions in imbalanced banking SR in the interpretation perspective.