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Under the dual pressure of resources and environment, many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society. This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice, and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation's ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.

This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology, management and structural reconstruction to reduce energy consumption and carbon emissions. Among them, the effect of structural energy conservation and emission reduction has become more prominent. It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors. The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.

Key aspects in improving energy efficiency include re-optimization of energy structure, re-innovation of energy-saving technologies and optimization of transportation organization. Path selection includes continuing to promote electrified railway construction, increasing the use of new and renewable energy sources, and promoting the reform of railway transportation organizations.

This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies, approaches for practice in a Chinese context. To achieve the expected goals, relevant supporting policies and measures need to be formulated, including actively guiding integrated transportation toward railway-oriented development, promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives, focusing on improving the energy efficiency of railways through market behavior. At the same time, it is necessary to pay attention to new phenomena in the railway industry for track and analysis.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The smart image sensor (SIS) which integrated with both sensor and smart processor has been widely applied in vision-based intelligent perception. In these applications, the linearity of the image sensor is crucial for better processing performance. However, the simple source-follower based readout circuit in the conventional SIS introduces significant nonlinearity. This paper aims to design a low-power in-pixel buffer circuit applied in the high-linearity SIS for the smart perception applications.

The linearity of the SIS is improved by eliminating the non-ideal effects of transistors and cancelling dynamic threshold voltage that changes with the process variation, voltage and temperature. A low parasitic capacitance low leakage switch is proposed to further improve the linearity of the buffer. Moreover, an area-efficient SIS architecture with a sharing mechanism is presented to further reduce the number of in-pixel transistors.

A low parasitic capacitance low leakage switch and a gate-source voltage pre-storage method are proposed to further improve the linearity of the buffer. Nonlinear effects introduced by parasitic capacitance switching leakage, etc., have been investigated and solved by proposing low-parasitic and low-leakage switches. The linearity is improved without a power-hungry operational amplifier-based calibration circuit and a noticeable power consumption increment.

The proposed design is implemented using a standard 0.18-µm CMOS process with the active area of 102 µm². At the power consumption of 5.6 µW, the measured linearity is −63 dB, which is nearly 27 dB better than conventional active pixel sensor (APS) implementation. The proposed low-power buffer circuit increase not only the performance of the SIS but also the lifetime of the smart perception system.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

The purpose of this paper is to quantitatively measure the vulnerability level of the whole rural social-ecological system in Yunnan Province and to analyze the spatial differences of the vulnerability in different regions.

Based on the “exposure-sensitivity-adaptability” vulnerability assessment framework, this paper establishes the index system of rural social-ecological system vulnerability to climate change. Combined with the questionnaire survey and meteorological data, the entropy method was used to measure and analyze the vulnerability level and influencing factors of the overall rural social-ecological system in Yunnan Province. At the same time, the vulnerability level of social-ecological system in Yunnan Province is divided into five levels, and the spatial differences of vulnerability level of 16 states (cities) in Yunnan Province are analyzed.

The results show that: the social-ecological system has high exposure to climate change (0.809), strong sensitivity (0.729), moderate adaptability (0.297) and overall system vulnerability is at a medium level (0.373). Yunnan Province is divided into five levels of social-ecological system vulnerable areas. The areas of extreme, severe, moderate, mild and slight vulnerability account for 21.45%, 24.65%, 36.82%, 13.18% and 3.90% of the whole province, respectively. The geographical division and vulnerability division of Yunnan Province are basically consistent in space.

Comprehensive evaluation of the vulnerability of the social-ecological system of Yunnan Province to climate change is the scientific basis for the country to formulate countermeasures against climate change, and it is also the need to improve the adaptability of the social and economic system of the fragile area, reduce the vulnerability and realize the sustainable development of national social economy. The research results can provide a basis for decision-making of climate adaptation in Yunnan and other regions and provide methods and indicators for the assessment of social-ecological system vulnerability under the background of climate change.