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The purpose of this paper is to prepare a water-resistant adhesive (SA) from soy flour (SF) with less water-soluble components.

Defatted SF was suspended and stirred in water. Then, the pH of dispersion was adjusted to a predetermined value (i.e. 8, 9 or 10) by the addition of 2M sodium hydroxide (NaOH) solution. After stirring at a predetermined temperature (25°C, 35°C, 45°C) for different time (1 h, 2 h, 3 h), the 2M hydrochloric acid (HCl) solution was added in a dropwise manner into the dispersion until the pH value was adjusted to 4.5. Then, the dispersion was centrifuged at 6,000 rpm for 2 min. The obtained precipitate with less water-soluble components was used as an adhesive (SA) directly.

SA had a wet strength of 1.02 MPa when used for the fabrication of poplar plywood. Polyvinyl alcohol (PVA) solution was applied to improve the tack of SAs to wood surface and the viscosities of SAs were decreased from 10,200 cP to 4,100 cP at room temperature after the PVA addition. The soy proteins in SAs were not denatured to a large extent according to the differential scanning calorimetry and light microscopy. The remained multilevel structures of soy protein played a positive contribution to the water resistance of SAs, and the bond lines of cured SAs were much more stable than those of the cured SF and soy protein concentrate (SPC).

The fluidity and solid content of soy adhesives is much lower than formaldehyde adhesives. Further investigations are needed to improve the fluidity of soy adhesives with high solid contents.

Novel water-resistant soy adhesives were provided.

This study examined the prevalence and relationship between addictive use of smartphones and symptoms of depression and anxiety among female undergraduates.

Standardized scales were used to measure the addictive use of smartphones, depression and anxiety among 398 female students (mean age 21.75 years, SD = 2.67) at two large higher institutions in southwest Nigeria and were opportunely sampled. Two hypotheses were tested using Spearman's rho and Mann–Whitney U tests.

The results showed that 1.01% of the respondents were probable smartphone addicts and 17.34% were at-risk, while 14.32% and 16.33% manifested symptoms of anxiety and moderate-to-severe depression, respectively. Depression (r = 0.24, p < 0.01) and anxiety (r = 0.21, p < 0.01) have significant relationship with addictive use of smartphone. Addictive/at-risk smartphone users significantly scored higher on symptoms of depression (average rank of 233.40) than normal smartphone users (average rank of 191.88); U = 9387.50; z = −2.81, p < 0.05; Also, addictive/at-risk smartphone users reported significantly higher level of anxiety (average rank of 229.27) than normal smartphone users (average rank of 192.81); U = 9689.00; z = −2.46, p < 0.05.

Generalizing these results to a clinical setting and other at-risk demographic groups might prove difficult due to the respondents' condition of homogeneity.

The findings suggest that relationships exist between the addictive use of smartphones and symptoms of depression and anxiety among undergraduate students in southwest Nigeria. Clinicians should assess smartphone use in the management of depression and anxiety disorders.

University administrators should target prevention and intervention strategies that would assist students to be taught positive ways of using their smartphones.

The study contributes to the body of knowledge by revealing relationships between smartphone addiction and mental health in an African sample.

The purpose of the article is to shed light on how COVID-19 affects employee involvement in environmental responsibility and innovative performance in the banking industry, and whether employee engagement mediates the relationship between the variables. Thus, this study tries to understand bank employees’ perspectives in relation to the variables.

The study was collected during Time lag (1) and Time lag (2) from 156 to 216 bank employees, respectively. The study applied two types of analysis, to comprehend the impact of COVID-19 on employees, descriptive analysis and the partial least squares (PLS) are used.

The study's findings focused mainly on the influence of COVID-19 in Jordanian banks on employee innovative performance (EIP) due to pandemic, in addition to its effect on environmental responsibility engagement (ERE). The findings indicated a positive significant relationship between the variables. Meanwhile, employee engagement (EE) mediated the effect between the exogenous and endogenous variables.

The current research provide light on the value of employees' innovative performance and banks' commitment to environmental responsibility for those working in the banking industry, particularly during a pandemic. The findings have significant ramifications for the banking industry and in raising employee engagement.

In this paper, a homogenization‐based multi‐scale method for predicting the effective thermal conductivity of porous materials with radiation is presented, which considers the effect of geometry and distribution of pores. Using homogenization method to solve the pure conductive problem of porous materials with periodic structure, the effective thermal conductivity without considering radiation is predicted, and a temperature field in a local domain of a unit cell is obtained. This temperature field is taken as the good approximation of the real temperature distribution, and the radiative thermal conductivity is obtained. The effect of the microstructure, the distribution and geometry of pores on heat transfer of porous materials is discussed. It is concluded that the dimension of the pores is an important influence factor on the thermal transfer property of porous materials if radiation is considered. Increasing the pore’s dimension enhances the contribution of radiation to the heat transfer property of porous materials. For porous materials with cylindrical and spherical pores, the radiative thermal conductivity is proportional to pore’s diameter.

Owing to the excellent performance, giant magnetostrictive materials (GMMs) are widely used in many engineering fields. The dynamic Jiles–Atherton (J-A) model, derived from physical mechanism, is often used to describe the hysteresis characteristics of GMM. However, this model, despite cited by many different literature studies, seems not to possess unique expressions, which may cause great trouble to the subsequent application. This paper aims to provide the rational expressions of the dynamic J-A model and propose a numerical computation scheme to obtain the model results with high accuracy and fast speed.

This paper analyzes different published papers and provides a reasonable form of the dynamic J-A model based on functional properties and physical explanations. Then, a numerical computation scheme, combining the Newton method and the explicit Adams method, is designed to solve the modified model. In addition, the error source and transmission path of the numerical solution are investigated, and the influence of model parameters on the calculation error is explored. Finally, some attempts are made to study the influence of numerical scheme parameters on the accuracy and time of the computation process. Subsequently, an optimization procedure is proposed.

A rational form of the dynamic J-A model is concluded in this paper. Using the proposed numerical calculation scheme, the maximum calculation error, while computing the modified model, can remain below 2 A/m under different model parameter combinations, and the computation time is always less than 0.5 s. After optimization, the calculation speed can be enhanced with the computation accuracy guaranteed.

To the best of the authors’ knowledge, this paper is the first one trying to provide a rational form of the dynamic J-A model among different citations. No other research studies focus on designing a detailed computation scheme targeting the fast and accurate calculation of this model as well. And the performance of the proposed calculation method is validated in different conditions.

The current study focuses on many risk categories that have emerged in the digital ecosystem of the financial technology industry, which has dramatically changed traditional financial systems as a result of innovations in financial technology.

The Web of Science Core Collection database was used to find a data set of 719 pertinent papers on the subject encompassing the year 2015–2023. The sample procedure was carried out utilising the PRISMA approach. The keywords were first gathered relating to technological risks in banking sectors and after confirming the keywords, the authors performed the search by the “topic” which covers “title” in the search bar. On February 15, 2023, the Web of Science database was searched using the terms “Cyber security risk OR data theft OR financial crimes OR financial stability risk OR operational risk OR default risk OR money laundering OR financial terrorism AND FinTech AND banking sector”. Two-step approach is applied in this study. First, descriptive analysis is applied using RStudio to highlight prominent authors, countries and affiliations. Furthermore, relationship among authors, countries and keywords is shown by using three fields plot. Second, using VOSviewer, co-occurrence of keyword analysis is used to determine the most influential themes.

The findings show that 2,611 documents have been published from 2016 to 2023. Year 2021 is the most productive year in terms of number of publications. The results also show that WANG XC is tied for the position of most prolific contributing author. In a similar vein, the United States leads the world in publication output. Furthermore, Southwestern University of Finance and Economics in China is leading the list with 15 articles. The results from the co-occurrence of keywords reveal that “default risk”, “operational risk”, “money laundering”, “credit risk”, “corporate governance”, “systematic risk”, “financial stability risk”, “risk management” and “crises” are the frequently keywords.

The results of this study are beneficial to academia and industry in order to advance their current understanding of FinTech and associated concerns. This work expands the understanding of the technology hazards facing the banking industry from a broad perspective.

A computational procedure is presented for the efficient non‐linear dynamic analysis of quasi‐symmetric structures. The procedure is based on approximating the unsymmetric response vectors, at each time step, by a linear combination of symmetric and antisymmetric vectors, each obtained using approximately half the degrees of freedom of the original model. A mixed formulation is used with the fundamental unknowns consisting of the internal forces (stress resultants), generalized displacements and velocity components. The spatial discretization is done by using the finite element method, and the governing semi‐discrete finite element equations are cast in the form of first‐order non‐linear ordinary differential equations. The temporal integration is performed by using implicit multistep integration operators. The resulting non‐linear algebraic equations, at each time step, are solved by using iterative techniques. The three key elements of the proposed procedure are: (a) use of mixed finite element models with independent shape functions for the stress resultants, generalized displacements, and velocity components and with the stress resultants allowed to be discontinuous at interelement boundaries; (b) operator splitting, or restructuring of the governing discrete equations of the structure to delineate the contributions to the symmetric and antisymmetric vectors constituting the response; and (c) use of a two‐level iterative process (with nested iteration loops) to generate the symmetric and antisymmetric components of the response vectors at each time step. The top‐ and bottom‐level iterations (outer and inner iterative loops) are performed by using the Newton—Raphson and the preconditioned conjugate gradient (PCG) techniques, respectively. The effectiveness of the proposed strategy is demonstrated by means of a numerical example and the potential of the strategy for solving more complex non‐linear problems is discussed.

The purpose of this paper is using a model-free reinforcement learning (RL) algorithm to optimize manipulability which can overcome difficulties of dilemmas of matrix inversion, complicated formula transformation and expensive calculation time.

Manipulability optimization is an effective way to solve the singularity problem arising in manipulator control. Some control schemes are proposed to optimize the manipulability during trajectory tracking, but they involve the dilemmas of matrix inversion, complicated formula transformation and expensive calculation time.

The redundant manipulator trained by RL can adjust its configuration in real-time to optimize the manipulability in an inverse-free manner while tracking the desired trajectory. Computer simulations and physics experiments demonstrate that compared with the existing methods, the average manipulability is increased by 58.9%, and the calculation time is reduced to 17.9%. Therefore, the proposed method effectively optimizes the manipulability, and the calculation time is significantly shortened.

To the best of the authors’ knowledge, this is the first method to optimize manipulability using RL during trajectory tracking. The authors compare their approach to existing singularity avoidance and manipulability maximization techniques, and prove that their method has better optimization effects and less computing time.

The purpose of this paper is to achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations.

To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function.

Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand.

This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.

This paper aims to clarify the effect of metal ions added in the γ-glycidoxypropyltrimethoxysilane (γ-GPS) solutions on the anti-corrosion properties of the γ-GPS coatings on cold-rolled iron (CRI).

The transformations of functional groups involved in reactions during the coating process were characterized by Fourier transformed infrared spectroscopy (FTIR), and the thickness of the γ-GPS coatings on the CRI substrates was measured using high-powered microscopy. The anti-corrosion properties of γ-GPS-treated samples were evaluated by neutral salt spray tests, polarization curves and electrochemical impedance spectroscopy measurements.

The results show that Zn2+ and Mg2+ in the γ-GPS solutions promote the formation of Si-O-Si and Si-O-Fe bonds and improve the anti-corrosion properties of the γ-GPS coatings on CRI. However, Al3+ and Na+ in the γ-GPS solutions do not play this role.

Although there have been previous research studies on the γ-GPS coatings on CRI, this paper is the first to study the effect of metal ions added in the silane solutions on the anti-corrosion properties of the γ-GPS coatings, and it has been confirmed that the anti-corrosion properties changed when Zn2+ (or Mg2+) is present.