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The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

Fatigue crack growth (FCG) tests on lead‐containing solders and lead‐free solders have been carried out at frequencies ranging from 0.01 to 10 Hz and stress ratios in the range 0.1–0.7. The FCG resistance of lead‐free solders was found to be superior to that of lead‐containing solders. For both types of solder, cycle dependent behaviour is dominant for the tests at low stress ratios and high frequencies, while time‐dependent effects become important at high stress ratios and low frequencies. For cycle dependent testing conditions, cracks primarily propagated in a transgranular manner, while a mixed trans/intergranular mode of crack propagation was observed for testing conditions where time dependent effects were dominant. The propagation path of intergranular cracks depended on the test materials, and along interfaces. After the FCG tests, the formation of small grains was observed.

This paper aims to study the issues of output reachable set estimation for the linear singular Markovian jump systems (SMJSs) with time-varying delay based on a proportional plus derivative (PD) bumpless transfer (BT) output feedback (OF) control scheme.

To begin with, a sufficient criterion is given in the form of a linear matrix inequality based on the Lyapunov stability theory. Then, a PD-BT OF controller is designed to keep all the output signs of the system are maintain within a predetermined ellipsoid. Finally, numerical and practical examples are used to demonstrate the efficiency of the approach.

Based on PD control and BT control method, an OF control strategy for the linear SMJSs with time-varying delay is proposed.

The output reachable set synthesis of linear SMJSs with time-varying delay can be solved by using the proposed approach. Besides, to obtain more general results, the restrictive assumptions of some parameters are removed. Furthermore, a sufficiently small ellipsoid can be obtained by the design scheme adopted in this paper, which reduces the conservatism of the existing results.

Firms are increasingly organizing cross-regional R&D collaborations among different units. Such collaborations should promote knowledge flows across distance and bring new knowledge to the local communities. However, the nature of cross-regional collaborations varies widely depending on the organizations within which they are organized. Compared with collaborations within small firms, collaborations in large firms tend to be routinized, which reduces the need for interpersonal interactions and increases the dependence on organizational structure. As a result, additional spillover from cross-regional collaboration is likely to be lower if the collaboration is within large firms. We extend this argument to the regional level and hypothesize that regions with a higher level of cross-regional collaborations tend to generate more valuable technologies, but when large firms dominate the formation of such collaborations, the marginal benefits of cross-regional collaboration are significantly reduced. Using a data set from the pharmaceutical industry between 1975 and 2001, we find support for our hypotheses. We conduct a series of robustness tests to check the consistency of our results.

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.

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.

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

This study examines the extent to which educational outcomes are transmitted from mothers to daughters in rural China. An analysis of the 2010 China Family Panel Survey reveals that: (i) how far daughters go in their education is strongly associated with their mothers’ education; (ii) the association between mothers’ and daughters’ educational outcomes in rural China was found to be stronger than the corresponding relationships between mothers and sons, fathers and daughters, and fathers and sons, especially at higher levels of education; and (iii) while having more brothers and being born later worsens daughters’ educational outcomes, mothers’ higher education effectively mitigates these negative effects. These findings add to a growing body of literature and empirical evidence that challenges conventional social mobility research paradigms that neglect mothers’ roles. More importantly, the distinction between mother–daughter relationship and that between fathers and daughters and mothers and sons highlights the fact that education is likely transmitted intergenerationally via mechanisms that differ depending on the gendered parent–child pairs.