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Based on the resource bricolage theory, we investigate the impact of proactive market orientation and responsive market orientation on firms’ disruptive green innovation. We also examine the impact of resource bricolage on disruptive green innovation and the mediating role of resource bricolage.

Quantitative data were collected from 232 firms in China. Structural equation modelling was used to test hypotheses.

The result show that proactive market orientation had positive effect on firm’s disruptive green innovation, whereas responsive market orientation had negative effect on firm’s disruptive green innovation. In addition, resource bricolage positively promotes firm’s disruptive green innovation. Resource bricolage played a mediating role between proactive market orientation and disruptive green innovation. Resource bricolage had a suppressing effect between responsive market orientation and disruptive green innovation.

This study makes up for the deficiency of the existing research on the relationship between market orientation and enterprise disruptive green innovation, improves the guidance mechanism of disruptive green innovation.

The purpose of this study was to evaluate the effects of repetitive transcranial magnetic stimulation (rTMS) at different frequencies on working memory (WM) and neuroelectric activity in rats.

Three rTMS protocols involving different frequencies were applied to rats, and 16-channel local field potentials (LFPs) and spikes were recorded from the prefrontal cortex (PFC) of rats in each group during the WM task. First, the behavior of rats during the T-maze task was analyzed, and then, the firing rate of spikes and the energy of the θ-band and γ-band in LFPs when rats performed the WM tasks were calculated. Finally, the spectral coherence between LFPs and spikes was analyzed by wavelet transform.

The results showed that rats in the stimulation groups needed fewer days than those in the control group to reach the task correction standard during the WM experiment (p < 0.05). High-frequency rTMS increases the firing rate of spikes and the degree of synchronization of LFPs-spikes in the θ-band and γ-band in the WM process.

This study showed that high-frequency rTMS can improve the spatial learning ability of rats, which might be due to the increased neuronal excitability of the PFC and the enhancement of co-coding between different modes of neural signals. This study is helpful for understanding the neuroregulatory mechanism of rTMS and will provide a reference for the selection of a suitable frequency for TMS treatment.

This study aims to research properties of Cu/SAC0307 mixed solder balls/Cu joints with different Zn-particles content at low-temperature under ultrasonic assisted.

A new method that 1µm Zn particles and Sn-0.3Ag-0.7 (SAC0307) with a particle size of 25–38 µm were mixed to fill the joint and successfully achieved micro-joining of Cu/Cu under ultrasonic-assisted at low temperature.

The results showed that with a continuous increase in the Zn-particle content, the interfacial intermetallic compounds (IMCs) of the upper and lower interfaces of joints gradually changed from scallop-shaped Cu₆Sn₅ to wavy-shaped Cu₅Zn₈. Moreover, the IMC thickness of the upper/lower interface of joints first decreased and then increased with increasing Zn-particle content. The shear strengths of joints increased with Zn-particle content, the shear strength of joints went to a maximum of 29.76 MPa when the Zn-particle content was 40%, an increase of 62.6% compared to joints without Zn particles. However, as the Zn-particle content continued to increase, the shear strengths of the joints decreased. Additionally, when the Zn content increased to 50%, because the oxidation degree of Zn particles increased, the joints were mainly broken among Zn particles.

A new method that 1µm Zn particles and Sn-0.3Ag-0.7 (SAC0307) with a particle size of 25–38 µm were mixed to fill the Cu/Cu joint at 180°C.

This study aims to evaluate the effect of thermal aging temperature on the properties of Cu/Al joints.

A new method in which 1 µm Zn-particles and SAC0307 with a particle size of 25–38 µm were mixed to fill the joint and successfully achieved the micro-joining of Cu/Al under ultrasonic-assisted at 200°C, and then, the effect of aging temperature on the properties of Cu/Al joints at different aging times was researched.

The results showed that the Cu interface intermetallic compounds (IMCs) had the same composition and had two layers with Cu₅Zn₈ near the Cu substrate and CuZn₅ near the solder. As the aging time increased, CuZn₅ gradually transformed to Cu₅Zn₈, and the thickness of the CuZn₅ layer gradually decreased until CuZn₅ disappeared completely. There was a Sn–Zn solid solution at the Al interface, and the composition of the Al interface of the Cu/Al joints did not change with changing temperature. The IMC thickness at the Cu interface of the joints continued to increase, and the shear strength of the Cu/Al joints decreased with increasing aging temperature and time. Compared with the as-received samples, the IMC thickness of the Cu interface of joints increased by 371.8% and the shear strength of the Cu/Al joints was reduced by 83.2% when the joints were aged at 150°C for 24 h. With an increase in aging temperature, the fracture mode of the Cu/Al joints changed from being between solder balls and Zn particles to between Zn particles.

With increasing aging temperature, the shear strengths of the Cu/SACZ/Al joints decreased at the same aging time, the shear strength of Cu/SACZ/Al joints at 150°C for 24h decreased by 83.2% compared with that of the as-received joints.

The purpose of this paper is to reveal the pattern between government innovation funding and enterprise value creation. Many factors, including government innovation funding, R&D ability, corporate governance and some company characteristics significantly affected the efficiency of firm value creation.

This paper proposed a novel methodology based on clustering-rough sets to explore the characteristics of enterprise value creation behavior, and map the relationship between government innovation funding and enterprise value creation. The agglomerative hierarchical clustering (AHC) algorithm were used to classify firm performance and get two types of value creation efficiencies and to discretize condition attributes because the rough set theory cannot deal with continuous attributes. This paper utilized the rough sets method to realize data mining and get rules of government innovation funding and enterprise value creation.

R&D ability, proportion of independent directors, remuneration of directors, operating revenue, number of employees, price-earnings ratio, quick ratio, capital intensity and ROA were important to identify firm value creation efficiency when government funded the firms. Firms of high level of government innovation funding, high lagged R&D ratio, high remuneration of directors, low price-earnings ratio, low quick ratio, moderate capital intensity and high ROA were more likely to have high efficiency of value creation.

Since China implemented the innovation-driven development strategy, facilitating enterprise innovation has become an important way to achieve high-quality economic growth. With constantly increasing of Chinese government innovation funding, studying on the effect of government innovation funding on firm’s value creation is significant to improve the efficiency of government resource allocation. It is valuable to reveal the pattern between government innovation funding and enterprise value creation based on the value added theory. The rules obtained could be used to provide decision-making support to improve the efficiency of government innovation funding and prevent waste of government resources effectively.