Search results

In order to alleviate China's crisis of marginalization in international trade, combined with the development characteristics of the Shanghai Free Trade Zone, the development direction of the bonded cold chain business of Shanghai Yangshan Comprehensive Bonded Port Area was proposed. From a long-term perspective, a free trade zone integrating processing, logistics, finance, culture, and internal and external market trade was formed. By taking advantage of the huge consumption of imported food in the Yangtze river delta region, the policy advantages of Yangshan Port Area are exploited. Combined with the development of cross-border e-commerce, innovative experiences that could be replicated and promoted are formed. The results showed that the free trade zone is the development direction of the bonded port area. Therefore, the Shanghai Bonded Port Area should focus on the integration with the development of the free trade zone in the initial stage. This lays a solid foundation for the construction of the bonded port area as a comprehensive internal and external trade platform for ASEAN (the Association of Southeast Asian Nations) and the domestic market. Research on the planning and layout of trade zones can help plan the future development of trade zones and their direction. The trade zone is pre-controlled. The efficiency of future construction and upgrading of the bonded area is improved. It is of great practical significance to the current development and construction of the Shanghai Bonded Port Area.

Since the reform and opening up, the economy of China has rapidly developed. The system, structure, mode, and pattern of the foreign trade in China must be adjusted accordingly to adapt to new economic normality. In this study, the main types of free trade areas worldwide were analyzed, and the necessary conditions for their successful development were examined on the basis of an ecological economic perspective. The Shanghai free trade area is a typical representative of a new type of Trade Zone in China. It introduces the principles of sustainable development, people oriented, green, low-carbon and other eco free trade zones. The planning characteristics of Shanghai free trade zone were studied from the point of view of planning economy and land use. Taking Shanghai Yangshan land free trade zone as an example, the planning research was carried out in terms of functional zoning, environment, transportation and facilities. In summary, this study provided theoretical and technical references for the construction of free trade areas and for the formulation of significant policies.

A large-scale detection system with more data in short time bins, small dead space and small signal identification is the ideology the scientists pursuing. These proposed demands are able to be solved by 2.5 D integration. The substance of a 2.5 D integration is called silicon interposer, which consists of the through silicon via (TSV) and redistribution layer. However, the state-of-the-art silicon interposer is not able to sustain its own mechanical strength with the detector/readout array often sitting as standalone in large science facilities and fails to reduce the expansions on the installation of the components due to its insufficient thickness and size. This study aims to propose a moderation of current interposer with large-sized, standalone properties.

This paper proposes an interposer based on double-sided silicon vias (DSSVs) interconnection. Unlike conventional interposer that is interconnected by TSVs, DSSVs interposer is interconnected by top vias (T-vias) and bottom vias (B-vias).

The fabrication process of DSSVs interposer is introduced, and the superiority of the double-sided interconnection process with two etch-stop layers is described in detail. The impact of different T-vias depth on DSSVs interconnections in the same wafer is discussed and two times PI opening processes are proposed to eliminate air bubbles in the B-via. The relationship between the interposer thickness and warpage is studied by finite element analysis simulation and experiment. The prototype of the DSSVs interposer with a size of 100  × 100 mm and a thickness of 318.2 µm is fabricated, and electrical tests including short tests and continuity tests are carried out.

This paper proposes a large-sized and stand-alone interposer based on DSSVs interconnection.

The purpose of this paper is to investigate thermal properties at Cu/Al interfaces.

A hybrid (molecular dynamics-interface stress element-finite element model (MD-ISE-FE) model is constructed to describe thermal behaviors at Cu/Al interfaces. The heat transfer simulation is performed after the non-ideal Cu/Al interface is constructed by diffusion bonding.

The simulation shows that the interfacial thermal resistance is decreasing with the increase of bonding temperature; while the interfacial region thickness and interfacial thermal conductivity are increasing with similar trends when the bonding temperature is increasing. It indicates that the higher bonding temperature can improve thermal properties of the interface structure.

The MD-ISE-FE model proposed in this paper is computationally efficient for interfacial heat transfer problems, and could be used in investigations of other interfacial behaviors of dissimilar materials. All these are helpful for the understanding of thermal properties of wire bonding interface structures. It implies that the MD-ISE-FE multiscale modeling approach would be a potential method for design and analysis of interfacial characteristics in micro/nano assembly.

This paper aims to introduce a method to reduce corrosion caused by acidic-oxidized polymer degradant through subsection injection with different inhibitor.

This paper introduced a method to reduce corrosion caused by acidic-oxidized polymer degradant through subsection injection with different inhibitor.

The experimental results indicated that the influence of pre-corrosion status on corrosion rate and effectiveness of corrosion inhibitor are significant. The corrosion inhibitors in both injection stage inhibited the corrosion process by preventing the contact of corrosive medium and steel surface through formation of a protective film on the surface of N80 steel. The corrosion rate of polymer degradant can be reduced to 0.63 g/m 2 h through subsection injection with different inhibitor.

This result will increase the production of polymer injection plugging wells through expanding the application of acidic-oxidized polymer degradant.

The purpose of this paper is to investigate the effects of political connections on the association between firms' business strategy and their tax aggressiveness in an emerging economy such as China.

The authors study a large sample of Chinese public firms from 2011 to 2017 using a panel regression model. In addition, a change analysis, an instrument variable test and alternative measures/samples are implemented as robustness tests.

Firms adopting innovative business strategy are more tax aggressive overall. However, innovative firms with political connections are less tax aggressive compared to those without political connections.

This paper contributes to the understanding of firms' tax behaviors in an emerging economy setting. It suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudies in the prior literature.

With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.

This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.

This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.

The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.

The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.

This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

This paper aims to explore the effects of normative and hedonic motivations on continuous knowledge contribution, and how past contribution experience moderates the effects of the motivations on continuous knowledge contribution.

Based on goal-framing theory, the present study proposes a comprehensive theoretical model by integrating normative and hedonic motivations, past contribution experience and continuous knowledge contribution. The data for virtual community members' activities were collected using the Python Scrapy crawler. Logit regression was used to validate the integrative model.

The results show that both normative motivation (reflected by generalized reciprocity and social learning) and hedonic motivation (reflected by peer recognition and online attractiveness) are positively associated with continuous knowledge contribution. Moreover, these effects are found to be significantly influenced by members' past knowledge contribution experience. Specifically, the results suggest that past knowledge contribution experience undermines the influence of generalized reciprocity on continuous knowledge contribution but strengthens the effect of peer recognition and online attractiveness.

Although the emerging literature on continuous knowledge contribution mainly focuses on motivations as antecedents that promote continuous knowledge contribution, most of these studies assume that the relationship between motivating mechanisms and continuous knowledge contribution does not change over time. The study is one of the initial studies to examine whether and how the influence of multiple motivations evolves relative to levels of past contribution experience.