The dynamics of the studies of China’s science, technology and innovation (STI): a bibliometric analysis of an emerging field

Since 1978, alongside China’s rise as a leading country in science, technology and innovation (STI), the studies of the country’s STI have been emerging as a field attracting increasing scholarly attention. Using the bibliometric method and the data from the Web of Science (WoS), this paper seeks to provide a comprehensive picture of the studies of China’s STI. The findings show that scholarly interests in China’s STI started in 1995 and have since developed rapidly; institutions in China, the U.S. and the U.K. are main contributors to the field, contributing 50%, 27.2% and 12% of the scholarship respectively, with Tsinghua University, Zhejiang University and the Chinese Academy of Sciences being three major institutional contributors. Seminal works have been focused on STI issues at the macro or national, meso or industrial and regional, and micro or organizational and firm levels. A possible agenda for further research is to develop new theories based on China’s practice paying specific attention to issues including R&D expenditure, S&T performance evaluation, regional innovation ecosystem, SOEs in innovation and the role of the Chinese Communist Party in innovation

The relation between the rheological properties of gels and the mechanical properties of their corresponding aerogels

A series of low density, highly porous clay/poly(vinyl alcohol) composite aerogels, incorporating ammonium alginate, were fabricated via a convenient and eco-friendly freeze drying method. It is significant to understand rheological properties of precursor gels because they directly affect the form of aerogels and their processing behaviors. The introduction of ammonium alginate impacted the rheological properties of colloidal gels and improved the mechanical performance of the subject aerogels. The specific compositions and processing conditions applied to those colloidal gel systems brought about different aerogel morphologies, which in turn translated into the observed mechanical properties. The bridge between gel rheologies and aerogel structures are established in the present workPostprint (published version

Performance study of fixed and moving relays for vehicular users with multi-cell handover under co-channel interference

In this paper, we investigate the power outage probability (OP) of a vehicular user equipment (VUE) device served by half-duplex decode-and-forward relay nodes (RNs) under co-channel interference. Both moving RNs (MRNs) and fixed RNs (FRNs) are studied, and compared with the baseline, base station (BS) to VUE direct transmission. In order to understand the benefit for vehicular users served by an RN, we consider practical channel models for different involved links as well as the impact of handover (HO) between the BS and the RNs. For an accurate comparison, we present a comprehensive framework to optimize the HO parameters, as well as we numerically optimize the FRN position which minimizes the average power OP at the VUE. FRN shows its advantage to serve its nearby VUEs. However, when vehicular penetration loss is moderate to high, MRN assisted transmission greatly outperforms transmission assisted by an FRN as well as direct transmission. Hence, the use of MRNs is very promising for improving the quality-of-service (QoS) of VUEs in future mobile communication systems

Radio Resource Management for D2D-based V2V Communication

Direct device-to-device (D2D) communication has been proposed as a possible enabler for vehicle-to-vehicle (V2V) applications, where the incurred intra-cell interference and the stringent latency and reliability requirements are challenging issues. In this paper, we investigate the radio resource management problem for D2D-based V2V communications. Firstly, we analyze and mathematically model the actual requirements for vehicular communications and traditional cellular links. Secondly, we propose a problem formulation to fulfill these requirements, and then a Separate Resource Block allocation and Power control (SRBP) algorithm to solve this problem. Finally, simulations are presented to illustrate the improved performance of the proposed SRBP scheme compared to some other existing methods

MOEA/D with Adaptive Weight Adjustment

Recently, MOEA/D (multi-objective evolutionary algorithm based on decomposition) has achieved great success in the field of evolutionary multi-objective optimization and has attracted a lot of attention. It decomposes a multi-objective optimization problem (MOP) into a set of scalar subproblems using uniformly distributed aggregation weight vectors and provides an excellent general algorithmic framework of evolutionary multi-objective optimization. Generally, the uniformity of weight vectors in MOEA/D can ensure the diversity of the Pareto optimal solutions, however, it cannot work as well when the target MOP has a complex Pareto front (PF; i.e., discontinuous PF or PF with sharp peak or low tail). To remedy this, we propose an improved MOEA/D with adaptive weight vector adjustment (MOEA/D-AWA). According to the analysis of the geometric relationship between the weight vectors and the optimal solutions under the Chebyshev decomposition scheme, a new weight vector initialization method and an adaptive weight vector adjustment strategy are introduced in MOEA/D-AWA. The weights are adjusted periodically so that the weights of subproblems can be redistributed adaptively to obtain better uniformity of solutions. Meanwhile, computing efforts devoted to subproblems with duplicate optimal solution can be saved. Moreover, an external elite population is introduced to help adding new subproblems into real sparse regions rather than pseudo sparse regions of the complex PF, that is, discontinuous regions of the PF. MOEA/D-AWA has been compared with four state of the art MOEAs, namely the original MOEA/D, Adaptive-MOEA/D, [Formula: see text]-MOEA/D, and NSGA-II on 10 widely used test problems, two newly constructed complex problems, and two many-objective problems. Experimental results indicate that MOEA/D-AWA outperforms the benchmark algorithms in terms of the IGD metric, particularly when the PF of the MOP is complex.</jats:p

D2D-based V2V Communications with Latency and Reliability Constraints

Direct device-to-device (D2D) communication has been proposed as a possible enabler for vehicle-to-vehicle (V2V) applications, where the incurred intra-cell interference and the stringent latency and reliability requirements are challenging issues. In this paper, we investigate the radio resource management problem for D2D-based V2V communications. Firstly, we analyze and mathematically model the actual requirements for vehicular communications and traditional cellular links. Secondly, we propose a problem formulation to fulfill these requirements, and then a Separate Resource Block allocation and Power control (SRBP) algorithm to solve this problem. Finally, simulations are presented to illustrate the improved performance of the proposed SRBP scheme compared to some other existing methods

Reducing Carbon Footprint Inequality of Household Consumption in Rural Areas:Analysis from Five Representative Provinces in China

Household consumption carbon footprint and inequality reductions are vital for a sustainable society, especially for rural areas. This study, focusing on rural China, one of the fastest growing economies with a massive population, explored the carbon footprint and inequality of household consumption using the latest micro household survey data of 2018 linked to environmental extended input–-output analysis. The results show that in 2018 in rural China, the average household carbon footprint is 2.46 tons CO2-eq per capita, which is around one-third of China’s average footprint, indicating the large potential for further growth. Housing (45.32%), transportation (20.45%), and food (19.62%) are the dominant contributors to the carbon footprint. Meanwhile, great inequality, with a Gini coefficient of 0.488, among rural households is observed, which is largely due to differences in type of house built or purchased (explaining 24.44% of the variation), heating (18.10%), car purchase (12.44%), and petrol consumption (12.44%). Provinces, average education, and nonfarm income are among the important factors influencing the inequality. In the process of urbanization and rural revitalization, there is a high possibility that the household carbon footprint continues to increase, maintaining high levels of inequality. The current energy transition toward less carbon-intensive fuels in rural China is likely to dampen the growth rates of carbon footprints and potentially decrease inequality. Carbon intensity decrease could significantly reduce carbon footprints, but increase inequality. More comprehensive measures to reduce carbon footprint and inequality are needed, including transitioning to clean energy, poverty alleviation, reduction of income inequality, and better health care coverage

Retentive Network: A Successor to Transformer for Large Language Models

In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-cost inference, and good performance. We theoretically derive the connection between recurrence and attention. Then we propose the retention mechanism for sequence modeling, which supports three computation paradigms, i.e., parallel, recurrent, and chunkwise recurrent. Specifically, the parallel representation allows for training parallelism. The recurrent representation enables low-cost $O(1)$ inference, which improves decoding throughput, latency, and GPU memory without sacrificing performance. The chunkwise recurrent representation facilitates efficient long-sequence modeling with linear complexity, where each chunk is encoded parallelly while recurrently summarizing the chunks. Experimental results on language modeling show that RetNet achieves favorable scaling results, parallel training, low-cost deployment, and efficient inference. The intriguing properties make RetNet a strong successor to Transformer for large language models. Code will be available at https://aka.ms/retnet