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This paper aims to investigate the effects of deposition time on the structure and anti-corrosion properties of a micro-arc oxidation (MAO)/Al coating on AZ31B Mg alloy.

The study describes the fabrication of the coating via a combined process of MAO with multi-arc ion plating. The structure, composition and corrosion resistance of the coatings were evaluated using scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction and electrochemical methods.

The Al-layer is tightly deposited with a good mechanical interlock along the rough interface due to the Al diffusion. However, the Al layer reduces the anti-corrosion of MAO-coated Mg alloy because of structural defects such as droplets and cavities, which act as channels for corrosive media infiltration towards the substrate. Fortunately, the Al layer improves the substrate corrosion resistance owing to its passive behaviour, and the corrosion resistance can be enhanced with increasing deposition time. All results indicate that a buffer layer fabricated through the duplex process improves the interfacial compatibility between the hard coating and soft Mg alloys.

An MAO/Al duplex coating was fabricated via a combined process of MAO and physical vapour deposition. MAO/Al duplex coatings exhibit obviously passive behaviours on AZ31 Mg alloy. The structure and corrosion resistance of MAO/Al coatings were investigated.

This study aims at addressing the impact of entrepreneurial education (EE) by highlighting career choice intentions (CCI) and entrepreneurial mindset (EM) as impact indicators, as well as unpacking the drivers and mediators in the formation of CCI among college students underpinned by social cognitive career theory (SCCT).

The hypotheses were tested on a survey sample of 1,198 students from 15 higher education institutions in China. Multinomial logistic regression was used to compare the different effects of EE on CCI, which is a categorical variable with four types of options.

The results confirmed the effects of EE on entrepreneurial self-efficacy (ESE), entrepreneurial outcome expectations (EOE) and EM, as well as the heterogeneity of antecedent connections with students preferring one career choice to the others. The results also revealed the mediating role of ESE and EOE in the model.

The study implies that ESE and EM should be integrated into EE learning outcomes and educators should focus on multiple career choice intentions rather than just entrepreneurial intention for college students' sustainable development.

The research contributes to the literature by verifying CCI and EM as impact indicators of EE, to a nuanced understanding of the educational development of various options of career paths by comparing different career intentions in a mediating model and to the expansion of SCCT by integrating diverse factors in a coherent model within the context of higher education in China.

This paper aim to investigate the influence of PA on the corrosion behavior of carbon steel with blast cleaned or pre-rusted treatments, and interpret the inhibition mechanism of PA on the steel with different surface treatments.

The influence of PA on the corrosion behavior of blast cleaned or rusty steel was investigated by means of electrochemical impedance spectroscopy (EIS). The EIS data were analyzed using the @ZsimpWin commercial software. The morphology and component of steel after immersion were characterized by scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), Fourier transformation infrared (FTIR) and X-ray diffractometer (XRD).

EIS analysis results indicated that PA had good corrosion inhibition for blast cleaned or rusty steel. SEM, EDS, FTIR and XRD further indicated that PA had two main corrosion inhibition processes for the corrosion inhibition of blast cleaned or rusty steel: corrosion dissolution and formation of protective barrier layers.

Most published works focus the attention only toward the effect of corrosion inhibitor for the clean metal surfaces. However, the surface condition of metal sometimes is unsatisfactory in the practical application of corrosion inhibitor, such as existing residual rust. Some studies also have shown that several corrosion inhibitors could be applied on partially rusted substrates. These inhibitors mainly include tannins and phosphoric acid, but not PA. Therefore, the authors investigated the influence of PA on the corrosion behavior of carbon steel with blast cleaned or pre-rusted treatments in this paper.

A high-boron concentration solution is commonly used as a buffer system in the study of metal corrosion. However, it is impossible to apply such a high-boron concentration solution in the practical use because of the high-cost and environment problem.

In this study, the authors examined the effect of a low dosage of boric acid and borax mixture as inhibitor to suppress carbon steel corrosion in 1 M HCl solution by weight loss experiment and various electrochemistry methods (potentiodynamic polarization curves, electrochemical impedance spectra and electrochemical noise).

Results showed that the borate mixture exhibited an anodic-type inhibitor characteristic, when the total boron concentration was in the range of 100∼150 mg L⁻¹. The passivation performance derived from the formation of a passive film with and FeBO₃-FeOOH structure, whose integrity and thickness gradually increased with the increasing boron concentration.

Low boron solution could protect carbon steel from the attraction of corrosive ions by forming a passive film with Fe-O-B structure. The findings broaden the application range of borate solution in the industry.

The purpose of this paper is to develop a familiarity analysis of resistive-capacitive (RC) network active circuit operating with unfamiliar low-pass (LP) type negative group delay (NGD) behavior. The design method of NGD circuit is validated by simulation with commercial tool and experimental measurement.

The present research work methodology is structured in three main parts. The familiarity theory of RC-network LP-NGD circuit is developed. The LP-NGD circuit parameters are expressed in function of the targeted time-advance. Then, the feasibility study is based on the theory, simulation and measurement result comparisons.

The RC-network based LP-NGD proof of concept is validated with −1 and −0.5 ms targeted time-advances after design, simulation, test and characterized. The LP-NGD circuit unity gain prototype presents NGD cut-off frequencies of about 269 and 569 Hz for the targeted time-advances, −1 and −0.5 ms, respectively. Bi-exponential and arbitrary waveform signals were tested to verify the targeted time-advance.

The performance of the unfamiliar LP-NGD topology developed in the present study is limited by the parasitic elements of constituting lumped components.

The NGD circuit enables to naturally reduce the undesired delay effect from the electronic and communication systems. The NGD circuit can be exploited to reduce the delay induced by electronic devices and system.

As social impacts of the NGD circuit application, the NGD function is one of prominent solutions to improve the technology performances of future electronic device in term of communication aspect and the transportation system.

The originality of the paper concerns the theoretical approach of the RC-network parameters in function of the targeted time-advance and the input signal bandwidth. In addition, the experimental results are also particularly original.

The study aims to investigate the anticorrosion performance of epoxy coatings using modified cerium oxide (CeO₂) by terephthalic acid (CeO₂-t) and fumaric acid (CeO₂-f) as corrosion inhibitors.

The chemical state of CeO₂-t, and CeO₂-f were analyzed by infrared radiation (IR) and X-ray diffraction (XRD). The effect of different inhibitors on the coating properties was analyzed by neutral salt spray tests (NSST) and electrochemical impedance spectroscopy (EIS).

The results of IR and XRD illustrate that the modification of CeO₂ was successful, and fumaric acid underwent a ring-opening reaction with epoxy resin (EP) in the coatings. The results of NSST and EIS showed that the coatings containing CeO₂-f exhibited the best anticorrosion performance.

CeO₂ is an effective inhibitor of the organic coatings. When surface modified, it is chemically bonded to EP, enhancing the anticorrosion performance of EP.

This paper aims to prepare a residual rust epoxy coating by adding different quantities of phytic acid (PA) on the surface of the rusty steel and investigate the corrosion protection of PA and its action mechanisms.

A residual rust epoxy coating by adding different quantities of PA was prepared on the surface of the rusty steel. The influence of PA on the corrosion resistance of epoxy-coated rusty steel was investigated by means of electrochemical impedance spectroscopy and adhesion testing.

Results indicated that PA can substantially improve the corrosion resistance of epoxy-coated rusty steel. This improvement is due to the reaction of PA with residual rust and generation of new compounds with protection properties and increased adhesive strength effects on the coating/metal interface. The coating showed better protection performance when 2 per cent PA was added.

Considering the structure of the active groups, PA has strong chelating capability with many metal ions and can form stable complex compounds on the surface of a metal substrate, thereby improving corrosion resistance. In recent years, PA has been reported to be useful in the conversion of coatings or as green corrosion inhibitor. To the best of the authors’ knowledge, few studies have reported the use of PA as a rust converter or residual rust coating. The present work aims to improve the corrosion resistance of residual rust epoxy coating by adding PA.

The purpose of this paper is to discuss the possibility and necessity of using grey system theory in neuropsychological studies.

The paper employs a logical analysis approach.

There are three characteristics of neuropsychological studies: the particularity of the study subjects; the specialty of the study scheme; and insufficient data from traditional statistical methods. Grey system theory is appropriate for analyzing the data collected in neuropsychological studies.

After several years' significant development, grey system theory has been applied in various subjects successfully. However, the application in psychology and medicine is still a rarity.

Science and technology policy plays an important role in promoting the development of economic and social development in China. At present, the research on science and technology policy is mainly focused on the basic theories and some quantitative research. The analyses for contents of massive science and technology policies are relatively less. This paper makes use of semantic technologies to extract and analyze the relatively important information from massive science and technology policies. The purpose of this paper is to facilitate users to quickly and effectively obtain valuable information from the massive science and technology policies. The key methods and study results are presented in the paper. The study results can provide references for further study and application in China.

The paper presented the analysis model and method for science and technology policy in China. The terms and sentences are the important information in the science and technology policy. The study adopted the technology of natural language processing to analyze the linguistics characteristics of terms and combined with statistical analyses to extract the terms from Chinese science and technology policy. Then, the authors designed an algorithm, calculated and analyzed the important sentences in Chinese science and technology policies. The experiments were run on the Java test platform.

This paper put forward the analysis model and method for science and technology policy in China. The study obtained the following conclusions: term extraction of science and technology policy: the paper analyzed characteristic of terms in Chinese science and technology policy and designed a method of extracting a term that was suitable for the science and technology policy. The calculation of important sentences for science and technology policy: the paper designed an algorithm and calculated the importance of the sentences to obtain valuable information from the massive science and technology policies.

In our methods, there are some defects to be improved or solved in the future. For example, the precision of algorithm needs to be improved. The significance of this paper is to propose and use the analysis model to process Chinese science and technology policy; we can provide an auxiliary tool to help policy beneficiaries. Enterprises and individuals can be more effective to extraction and mining information from massive science and technology policy and find the target policy.

To verify the effectiveness of the method, the paper selected the real policies about the new energy vehicles as experimental data; at the same time, the paper added uncorrelated policies. It used the proposed analysis model of science and technology policy to calculate and find out the relatively important sentences. The results of study showed that the proposed method can obtain better performance. It verified the validity of this method. The model and method have been applied to actual retrieval system.

The proposed model and method in the paper have been applied to actual retrieval system for users.

The paper proposed the new analysis model and method to analyze science and technology policies in China. The presented model and method are a new attempt. According to the experimental results, this exploration and study are valuable. In addition, the idea and method will give a good start for improving information services of massive science and technology policies in China.

This study aims to clarify the effect of team effort allocation between knowledge exploration and exploitation on the generation of extremely good or poor innovations. The influence of previous collaborative experience among team members on the effect of team effort allocation is also investigated to understand the relationship between team members’ collaboration networks and knowledge learning.

This study uses data of all patents granted by the US Patent and Trademark Office between 1984 and 2010. The inventors involved in a patent are regarded as members of the focal team. Logistic regression is used to analyze the data.

Allocating greater effort to exploration than to exploitation is beneficial to achieving breakthrough innovations despite the risk of generating particularly poor innovations. This benefit increases with collaborative experience among team members. Placing an equal emphasis on knowledge exploration and exploitation is not particularly effective in achieving breakthrough innovations; it is, however, the best strategy for avoiding particularly poor innovations.

This research not only provides valuable insights for research on innovation and knowledge management by studying the team effort allocation strategy used to achieve breakthroughs and avoid particularly poor innovations but also represents an advancement in bridging two streams of research – knowledge learning and social networks – by highlighting the influence of the team members’ collaborative networks on the effect of team effort allocation between knowledge exploration and exploitation.