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Deep learning techniques are unavoidable in a variety of domains such as health care, computer vision, cyber-security and so on. These algorithms demand high data transfers but require bottlenecks in achieving the high speed and low latency synchronization while being implemented in the real hardware architectures. Though direct memory access controller (DMAC) has gained a brighter light of research for achieving bulk data transfers, existing direct memory access (DMA) systems continue to face the challenges of achieving high-speed communication. The purpose of this study is to develop an adaptive-configured DMA architecture for bulk data transfer with high throughput and less time-delayed computation.

The proposed methodology consists of a heterogeneous computing system integrated with specialized hardware and software. For the hardware, the authors propose an field programmable gate array (FPGA)-based DMAC, which transfers the data to the graphics processing unit (GPU) using PCI-Express. The workload characterization technique is designed using Python software and is implementable for the advanced risk machine Cortex architecture with a suitable communication interface. This module offloads the input streams of data to the FPGA and initiates the FPGA for the control flow of data to the GPU that can achieve efficient processing.

This paper presents an evaluation of a configurable workload-based DMA controller for collecting the data from the input devices and concurrently applying it to the GPU architecture, bypassing the hardware and software extraneous copies and bottlenecks via PCI Express. It also investigates the usage of adaptive DMA memory buffer allocation and workload characterization techniques. The proposed DMA architecture is compared with the other existing DMA architectures in which the performance of the proposed DMAC outperforms traditional DMA by achieving 96% throughput and 50% less latency synchronization.

The proposed gated recurrent unit has produced 95.6% accuracy in characterization of the workloads into heavy, medium and normal. The proposed model has outperformed the other algorithms and proves its strength for workload characterization.

This paper aims to investigate the effect of corporate environmental disclosure on earnings management and to further examine whether this relationship is moderated by female board.

Our sample includes 264 European companies listed on the STOXX eUROPE 600 for the period 2010 to 2022. We excluded financial companies (banks and insurance companies) due to their specific capital structure and regulatory requirements, and companies with missing data. Feasible Generalized Least Square (FGLS) regression method is used to estimate the econometric models. For robustness analyses, the authors included the alternative measure of the dependent variable, and they applied the simultaneous equation model for the endogeneity test.

Using discretionary accruals as a proxy for earnings management, the results obtained indicated a negative effect of corporate environmental disclosure on earnings management. The results suggest also that women on boards are effective in their monitoring role. Indeed, findings show that the effect of corporate environmental disclosure on earnings management is particularly stronger with the presence of women directors on the companies’ boards.

This study has two limitations. Firstly, the sample size is relatively small, which may limit the generalizability of our findings. Secondly, our earnings management indicator, based on estimates of accruals, may not perfectly reflect all streams of earnings management. Therefore, to reduce potential bias in these estimates, it would be useful to use other indicators, such as real earnings management.

The findings have several implications for regulatory, investors and academic researchers. For regulators, it is appropriate to promote several standards related to corporate environmental disclosure and earnings management. The results advise also the worldwide policy maker to give the importance of female roles to improve engagement firms in corporate environmental disclosure, so to be more transparent in their accounting practices to ensure that they are not engaging in unethical or fraudulent behavior. For investors, the results show that the existence of female directors on the board reduces earnings management. For academic researchers, it is interesting to explore the relationship between corporate environmental disclosure, women on the board, and earnings management.

This paper extends the existing literature by examining the moderating effect of women directors on the relationship between corporate environmental disclosure and earnings management in the European context.

While the theory and practice of open innovation networks are flourishing, green innovation in manufacturing small and medium-sized enterprises (SMEs) is stagnant. This study explores the mechanism driving green innovation in manufacturing SMEs under open innovation networks based on the role of innovation platforms' relational governance.

A quantitative study was conducted using questionnaires to collect data from 270 manufacturing SMEs in Zhejiang Province and employing a structural equation model to test the developed hypotheses.

The results revealed that innovation platforms' relational governance positively affects green innovation in manufacturing SMEs. Furthermore, the collaborative innovation atmosphere and risk perception mediate this relationship through a respective mediating role and a chain-mediating role.

This study is the first to empirically investigate the mechanism of the influence of innovation platforms' relational governance on green innovation in manufacturing SMEs, provide a new perspective for understanding the antecedents of green innovation under open innovation networks, and expand the theoretical research on open innovation management.

The purpose of our study is to investigate the effects of politically-connected boards (PCBs) on over-(under-)investment in labor. We also examine the impacts of the supervisory board (SB)’s optimal tenure on the association between PCBs and over-investment in labor.

We constructed the proxy for PCBs using a dummy variable set to 1 (one) if a firm has politically-connected boards and zero (0) otherwise. For the robustness check, we used the number of politically-connected members on the boards as the proxy for PCBs.

We find that the presence of PCBs reduces over-investment in labor. Consistent with our prediction, we found no significant association between PCBs and under-investment in labor. We also find that the SB with optimal tenure strengthens the negative association between PCBs and over-investment in labor. In our channel analysis, we find that the presence of PCB mitigates over-investment in labor through a higher dividend payout ratio.

Due to the unavailability of data in firms’ annual reports regarding the number of poorly-skilled and highly skilled employees, we were not able to examine the effect of low-skilled and high-skilled employees on over-investment in labor. Also, we were not able to examine over-(under-)investment in labor by drawing a distinction between general (generalist) and firm-specific human capital (specialist) as suggested by Sevcenko, Wu, and Kacperczyk (2022). Generally, it is more difficult for managers to hire highly-skilled employees, specialists in particular, thereby driving the choice of either over- or under-investing in the labor forces. In addition, in the firms’ annual reports, there is no information regarding temporary employees. Therefore, if and when such data become available, this would provide another avenue for future research.

Our study offers several practical implications and insights to stakeholders (e.g. insiders or management, shareholders, investors, analysts and creditors) in the following ways. First, our study highlights significant differences between capital investment and labor investment. For instance, labor investment is considered an expense rather than an asset (Wyatt, 2008) because, although such investment is human capital and is not recognized on the firm’s balance sheet (Boon et al., 2017). In addition, labor investment is characterized by: its flexibility which enables firms to make frequent adjustments (Hamermesh, 1995; Dixit & Pindyck, 2012; Aksin et al., 2015), its non-homogeneity since every employee is unique (Luo et al., 2020), its direct impact on morale and productivity of a firm (Azadegan et al., 2013; Mishina et al., 2004; Tatikonda et al., 2013), and its financial outlay which affects the ongoing cash flows of a firm (Sualihu et al., 2021; Khedmati et al., 2020; Merz & Yashiv, 2007). Second, our findings reveal that the presence of PCBs could help to reduce over-investment in labor. However, if managers of a firm choose to under-invest in labor in order to obtain better profit in the short-term through cost saving, they should be aware of the potential consequences of facing a financial loss when a new business opportunity suddenly arises which requires a larger labor force. Third, our findings help stakeholders to re-focus on the labor investment. This is crucial due to the fact that labor investment is often neglected by those stakeholders because the expenditure of labor investment is not recognized on the firm’s balance sheet as an asset. Instead, it is written off as an expense in the firm’s income statement. Fourth, our findings also provide insightful information to stakeholders, suggesting that an SB with optimal tenure is more committed to a firm, and this factor plays an important role in strengthening the negative association between PCBs and over-investment in labor.

First, our findings provide a valuable understanding of the effects of PCBs on over-(under-)investment in labor. Stakeholders could use information disclosed in the financial statements of a publicly-listed firm to determine the extent of the firm’s investment in labor and PCBs, and compare this information with similar firms in the same industry sector. Second, our findings give a better understanding of the association between investment in labor and political connections , which are human and social capital that could determine the long-term survival and success of a firm. Third, for shareholders, the appointment of board members with political connections is an important strategic decision to build political capital, which is likely to have a long-term impact on the financial performance of a firm; therefore, it requires thoughtful consultation with firm insiders.

Our findings highlight the role of PCBs in reducing over-investment in labor. These findings are significant because both investment in labor and political connections as human and social capital can play an important role in determining the long-term survival and success of a firm.

Ascorbic acid, a water-soluble antioxidant, is an essential component of the human diet and is known for its potent antioxidant properties against several diseases. In recent years, there has been increasing interest in the development of nonenzymatic sensors due to their simplicity, efficiency and excellent selectivity. The aim of this study is to present a selective and sensitive method for the detection of ascorbic acid in aqueous system using a new electrochemical non-enzymatic sensor based on a gold nanoparticles Au-NPs-1,3-di(4-bromophényl)-5-tert-butyl-1,3,5-triazinane (DBTTA) composite.

Using the square wave voltammetry (SWV) technique, a series of Au-NPs-DBTTA composites were successfully developed and investigated. First, DBTTA was synthesized via the condensation of tert-butylamine and a4-bromoaniline. The structure obtained was identified by IR, 1H NMR and 13C NMR analysis. A glassy carbon electrode (GCE) was modified with 10–1 M DBTTA dissolved in an aqueous solution by cyclic voltammetry in the potential range of 1–1.4 V. Au-NPs were then deposited on the DBTTA/GCE by a chronoamperometric technique. SWV was used to study the electrochemical behavior of the modified electrode (DBTTA/Au-NPs/GCEs). To observe the effect of nanoparticles, ascorbic acid in a buffer solution was analyzed by SWV at the modified electrode with and without gold nanoparticles (Au-NPs).

The DBTTA/Au-NPs/GCE showed better electroanalytical results. The detection limit of 10–5 M was obtained and the electrode was proportional to the logarithm of the AA concentration in the range of 5 × 10⁻³ M to 1 × 10⁻¹ with very good correlation parameters.

It was also found that the elaborated sensor exhibited reproducibility and excellent selectivity against interfering molecules such as uric acid, aspartic acid and glucose. The proposed sensor was tested for the recognition of AA in orange, and satisfactory results were obtained.

This study aims to investigate the linkage of employee treatment and trade credit for a sample of 45 countries from 2003 to 2018. It explores the trade credit from a receivable perspective.

The estimations are performed using panel regression with fixed effects for both country and year. A batter of robustness tests is also performed to validate the findings.

The results reveal a positive and highly significant relation between employee treatment and trade credit. The authors observe that firms from labor-intensive and highly competitive industries are likelier to extend trade credit to their customers. The authors also find that firms from developed countries are more likely to extend trade credit to their customers.

First, to boost trade credit, the firms need to materialize fair employee treatment. Second, firms from labor-intensive firms and highly competitive industries need to care more about employee treatment which promotes trade credit.

The findings offer novel evidence of the relationship between employee treatment and trade receivables.

This study aims to explore the relationship between non-market strategies and organizational resilience, using a Chinese private enterprise as an example.

This study collected data through semi-structured interviews and analyzed them through grounded theory, using a three-step approach of open coding, axial coding and selective coding to analyze and construct a model of the mechanism of the impact of non-market strategies on organizational resilience.

The following conclusions were drawn from this study. (1) Stakeholders, internal and external environment and entrepreneurship are important motivations that influence private firms to implement non-market strategies to enhance organizational resilience, with entrepreneurship being the key driver. (2) Non-market strategies contain three dimensions, and different non-market behaviors have different mechanisms of action on the organizational resilience of firms. (3) Non-market strategies and organizational resilience form an interactive spiral relationship. This mutually reinforcing effect promotes firm growth and sustainable corporate development. The research results enrich the theoretical connotation of non-market strategies, construct a model of the mechanism of influence of non-market strategies on organizational resilience, and describe three explanatory paths for the relationship between the two–incentive mechanism, functional mechanism and transformation mechanism.

This study's single case is unique and based on the Chinese context. In addition, this study adopts a rooted qualitative research approach and although the coding and model construction strictly follow the steps of grounded theory research, a degree of subjectivity is inevitable. On this basis, future research can adopt quantitative analysis methods to test and improve the model.

This paper explores the important role of non-market strategies in the Chinese context under the impact of traditional market mechanisms, based on the perspective of Chinese private enterprises, and provides new insights and revelations for private enterprises to achieve sustainable development.

This study innovatively explores the formation mechanism of organizational resilience from the perspective of non-market strategies, adding a new perspective to the literature. Additionally, it examines the mechanisms between long-term non-market strategy and organizational resilience, particularly their relationship in times of crisis, utilizing a rooted approach that goes beyond static analysis.

The purpose of this study is to optimize and improve conventional welding using EMF assisted technology. Current industrial production has put forward higher requirements for welding technology, so the optimization and improvement of traditional welding methods become urgent needs.

External magnetic field assisted welding is an emerging technology in recent years, acting in a non-contact manner on the welding. The action of electromagnetic forces on the arc plasma leads to significant changes in the arc behavior, which affects the droplet transfer and molten pool formation and ultimately improve the weld seam formation and joint quality.

In this paper, different types of external magnetic fields are analyzed and summarized, which mainly include external transverse magnetic field, external longitudinal magnetic field and external cusp magnetic field. The research progress of welding behavior under the effect of external magnetic field is described, including the effect of external magnetic field on arc morphology, droplet transfer and weld seam formation law.

However, due to the extremely complex physical processes under the action of the external magnetic field, the mechanism of physical fields such as heat, force and electromagnetism in the welding has not been thoroughly analyzed, in-depth theoretical and numerical studies become urgent.

Following the COVID-19 pandemic, most higher education institutes shifted to online learning as the sole alternative to continuing education while mitigating the risks imposed by the pandemic. This has raised several concerns regarding students’ learning experience, satisfaction and academic achievement, particularly in countries where students have restrained technological resources (i.e. developing nations). The current research aims to investigate the key factors influencing students’ attitudes, satisfaction and academic achievement among university students in an emerging market context (i.e. Morocco). The moderating effect of students’ motivation to study online was also scrutinized.

The authors propose an integrated conceptual framework that combines the technology acceptance model (TAM) with the outcomes of prior literature related to online learning. Based on data collected from 850 Moroccan university students, the authors empirically tested the conceptual model using a partial least squares (PLS) estimation.

First, attitude toward online learning and satisfaction positively impact university students’ academic achievement; at the same time, attitude positively impacts students’ satisfaction with online learning. Second, students’ satisfaction and attitude toward online learning were found to be mainly influenced by instructor performance, ease of use of the online learning platform, information quality, interactivity and perceived usefulness (PU). Finally, student motivation acts as a moderator, e.g. students with higher motivation to learn online are more likely to develop a favorable attitude toward online learning and can, therefore, accomplish better academic performance.

The current study makes a considerable contribution to the literature by contributing to the on-going debate about the potentials and challenges of online learning, particularly in an emerging country where education remains a considerable challenge. The study findings can help higher education institutes gauge the quality of online education programs and design efficient strategies to develop high-quality online learning for students. Our findings have implications not only for educational institutions and instructors in developing markets but also for the vendors of online course delivery software.

The embedding of digital technology and the fuzzy organizational boundary have changed the operation of platform innovation ecosystem (PIE). Specifically, as an important energy of PIE, the internal logic of knowledge flow needs to be reconsidered in the context of digital age, which will be helpful to select the cultivation and governance strategy of PIE.

A dual case-analysis is applied to open the “black box” of knowledge flow in the PIE from the perspective of enabled by digital technology, by taking the intellectual property (IP) operation platform as cases.

The research findings are as follow: (1) The knowledge flow mechanism of PIE is mainly demonstrated through the processes of knowledge acquisition, knowledge integration and knowledge spillover. During this process, connectivity empowerment and scenario empowerment realize the digital empowerment of the platform. (2) Connectivity empowerment provides a channel of knowledge acquisition for the digital connection between participants in PIE. In the process of knowledge integration, scenario empowerment improves the opportunities for accurate matching and collaborative innovation between knowledge supplier and demander, and enhance the value of knowledge. The dual effect of connectivity empowerment and scenario empowerment has accelerated the knowledge spillover in PIE. Particularly, connectivity empowerment expands the range of knowledge spillover, and scenario empowerment affects the generativity of the platform, resulting in the enhancement of platform’s capability to embed and expand its value network. (3) Participants have been benefitted from the PIE enabled by digital technology through three key modules (knowledge acquisition, knowledge integration and knowledge spillover), as the result of knowledge flow.

This study focuses on the knowledge flow mechanism of PIE enabled by digital technology, which enriches the PIE theory, and has enlightenments for the cultivation of digital platform ecosystem.