Search results

Based on DNase I and reduced graphene oxide (rGO)-magnetic silicon microspheres (MNPS), a highly sensitive and selective fluorescent probe for the detection of PD-L1 was developed.

Here °C we present a feasibility of biosensor to detection of PD-L1 in lung tumors plasma. In the absence of PD-L1°C the PD-L1 aptamer is absorbed on the surface of graphene oxide modified magnetic nanoparticles °8rGO-MNPS°9 and leading to effective fluorescence quenching. Upon adding PD-L1°C the aptamer sequences could be specifically recognized by PD-L1 and the aptamer/PD-L1 complex is formed°C resulting in the recovery of quenched fluorescence.

This sensor can detect PD-L1 with a linear range from 100 pg mL⁻¹ to 100 ng mL⁻¹, and a detection limit of 10 pg•m⁻¹ was achieved.

This method provides an easy and sensitive method for the detection of PD-L1 and will be beneficial to the early diagnosis and prognosis of tumors.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

Due to recent technological advances, the retail industry has changed significantly. This paper examines a novel unmanned retail mode-unattended convenience store to identify the possible operational problems and develop appropriate managerial recommendations.

A data-driven two-stage epsilon-based measure (EBM) data envelopment analysis (DEA) method was developed to evaluate operational performance data from 33 unattended convenience stores and assess the impacts on efficiency of the internal factors, and a Tobit regression analysis was employed to examine the external environment.

It was found that the overall economic performances were relatively low and fluctuated significantly; however, the social performances were slightly higher. The out-of-stock rate was found to have a negative impact on efficiency, and regional characteristics were found to have significant effects on performance.

This study sought to identify current operational problems with unattended convenience stores to provide managerial insights. The cross-sectional assessment suggested that to achieve better performance, particular attention needed to be paid to store locations and surrounding store environments.

First, this paper establishes a novel theoretical framework to evaluate the economic and social operational performances at unattended convenience stores. Second, it contributes to research on unattended convenience stores and the unmanned retail industry and offers significant guidance on detecting operational deficiencies and improving future performances.

This study aims to investigate the effects of graphite-MoS₂ composite solid lubricant on the tribological properties of copper-based bearing materials under dry conditions.

The mixture of Graphite-MoS₂ was inlaid in ZQSn6-6–3 tin bronze and ZQAl9-4 aluminum bronze matrix. These copper-embedded self-lubricating bearing materials were considered in friction pairs with 2Cr13 stainless steel, and their tribological properties were studied by using an MM200 wear test machine.

The results show that the friction coefficients and wear rates of copper-embedded self-lubricating bearing materials are lower than those of the ordinary copper-based bearing materials. The wear performance of the tin bronze inlaid self-lubricating bearing material is better than that of the aluminum bronze inlaid self-lubricating bearing material. The wear mechanism of the tin bronze bearing material is mainly adhesive wear, and that of the aluminum bronze bearing material is mainly grinding wear, oxidation wear and adhesive wear. The copper-embedded self-lubricating bearing materials had no obvious abrasion, whereas the aluminum bronze inlaid self-lubricating bearing material exhibited deep furrows and obvious abrasion under high loads.

These results are helpful for the application of copper-embedded self-lubricating bearing materials.

In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

Drawing upon social information processing theory, this study investigates the correlation between self-serving leadership and employee expediency. It also explores the mediating effect of self-interest motivation and the moderating effect of trait mindfulness.

A total of 147 part-time MBA students were enlisted to participate in a scenario experiment (Study 1), and 291 valid employee questionnaires were collected through a multiple-time point survey (Study 2). SPSS 23.0, MPLUS 8.0 and PROCESS programs were used to analyze the data and test the hypotheses.

Study 1 illustrated a positive correlation between self-serving leadership and employee expediency. It also identified self-interest motivation as a mediating factor in the correlation between self-serving leadership and expediency. Study 2 replicated the results obtained in Study 1 and expanded upon them by demonstrating that trait mindfulness moderates the association between self-serving leadership and self-interest motivation. Additionally, trait mindfulness moderates the indirect effect of self-serving leadership on expediency.

This research argues that organizations should take steps to prevent self-serving leadership in order to reduce employee expediency. Furthermore, it is advisable to provide ethics training to employees who exhibit high trait mindfulness, as they show increased sensitivity to self-serving leadership and are more likely to engage in unethical behavior.

This study expands the existing research on the ethical outcomes of self-serving leadership and contributes to a deeper understanding of the negative aspects of trait mindfulness.

This paper aims to study the issues of output reachable set estimation for the linear singular Markovian jump systems (SMJSs) with time-varying delay based on a proportional plus derivative (PD) bumpless transfer (BT) output feedback (OF) control scheme.

To begin with, a sufficient criterion is given in the form of a linear matrix inequality based on the Lyapunov stability theory. Then, a PD-BT OF controller is designed to keep all the output signs of the system are maintain within a predetermined ellipsoid. Finally, numerical and practical examples are used to demonstrate the efficiency of the approach.

Based on PD control and BT control method, an OF control strategy for the linear SMJSs with time-varying delay is proposed.

The output reachable set synthesis of linear SMJSs with time-varying delay can be solved by using the proposed approach. Besides, to obtain more general results, the restrictive assumptions of some parameters are removed. Furthermore, a sufficiently small ellipsoid can be obtained by the design scheme adopted in this paper, which reduces the conservatism of the existing results.

Confucianism underpins Chinese traditional culture and the values of the Chinese people. The purpose of this study is to examine the relationship between adherence to Confucianism and corporate irregularities.

The authors use the historical numbers of Jinshi (Imperial Scholars) in the Ming and Qing dynasties within 200 km of a company's location to proxy for the influence of Confucianism on the company, presenting strong evidence that Confucianism significantly reduces corporate irregularities.

The authors' findings are robust even when criticized with alternative definitions of Confucianism, sensitivity analysis and instrumental variable regression. The authors also discover that this effect is weaker in state-owned and foreign enterprises and weakened by the influence of Western culture.

This paper brings a new traditional-cultural perspective to the understanding of corporate irregularities and contributes to the literature on culture and finance. This paper also helps the authors understand the “China Puzzle” that is China's rapid economic development under an imperfect legal system.

This paper aims to examine the optimal promotion strategy of an e-retailer, who may advertise, or launch rebates initiative to encourage consumers' disseminating electronic word-of-mouth (eWOM) messages, with an aim to boost product sales.

This paper analyzes the decisions of the e-retailer in a two-period model, using utility function approach and backward induction method, and obtains the optimal solutions in four promotion strategies.

The study finds that rebate scheme greatly impacts the timing of advertising, and neither lower nor higher consumers' eWOM effort invariably benefits the retailer, rather, a medium level is the best choice for the retailer. When eWOM impact power is at a relatively high level, it can supplement advertising effect to attract more consumers' purchase. Otherwise, eWOM may counteract the role of advertising.

Different from the extant literature focusing on advertising or eWOM without rebates, the paper studies the issue of advertising and eWOM with rebates in two- period model which seldom addresses before the authors examine the optimal timing of advertising and eWOM with/without rebates in four promotion strategies i.e. the A-NE model the NE-A model the A-ER model and the ER-A model.

The link between interlocking directors and mergers and acquisitions (M&A) efficiency has been analyzed in an information asymmetry environment. Despite an abundance of evidence highlighting that interlocking directors do contribute to M&A efficiency in an acquirer-target binary relationship, the target is embedded in a complex network of supplier-customer relationships, which implies that the acquirer needs to consider the value of suppliers, distributors and retailers in the target’s supply chain in improving M&A efficiency. Through the lenses of acquirer-target multivariate relationships, this paper aims to examine how directors with supply chain experience (DSCs) act as heterogeneous network pipes to affect M&A efficiency.

Using a sample of 311 A-share listed firms on the Shanghai and Shenzhen stock exchanges in China during 2011–2020, this paper investigates the relationship between DSCs and M&A efficiency by using ordinary least squares (OLS) regression.

Through empirical research, we verify a negative relationship between DSCs and M&A duration and an inverted U-shaped relationship between both DSCs and M&A performance, revealing the complexity of the relationship between experience and efficiency. Furthermore, drawing on upper echelon theory, the information value of DSCs will be greatly reduced when executives have overconfident psychological characteristics, which are mainly shown to negatively moderate the relationship between DSCs and M&A performance. We also conduct multiple robustness tests and supplemental analyses to illustrate the robustness and boundaries of our findings. Finally, DSCs are likely more important in environments among growth and mature firms as well as high-growth industries.

We break through the assumption that interlocking directors contribute to M&A efficiency in an acquirer-target binary relationship and examine the impact of DSCs on M&A efficiency based on micro-empirical evidence from the value of target-related upstream or downstream industries, which extends the connotation of interlocking directors and enriches the study related to factors influencing M&A efficiency.