PGN: A perturbation generation network against deep reinforcement learning

Deep reinforcement learning has advanced greatly and applied in many areas. In this paper, we explore the vulnerability of deep reinforcement learning by proposing a novel generative model for creating effective adversarial examples to attack the agent. Our proposed model can achieve both targeted attacks and untargeted attacks. Considering the specificity of deep reinforcement learning, we propose the action consistency ratio as a measure of stealthiness, and a new measurement index of effectiveness and stealthiness. Experiment results show that our method can ensure the effectiveness and stealthiness of attack compared with other algorithms. Moreover, our methods are considerably faster and thus can achieve rapid and efficient verification of the vulnerability of deep reinforcement learning

Impact Assessment of New Energy Characteristics on Regional Power Grid Considering Multiple Time Scales

[Introduction] With the development of new energy, the influence of new energy uncertainty and time characteristics on power grid is increasing day by day. Traditional new energy indexes are difficult to describe the interaction between power grid and new energy. It is necessary to establish evaluation system and index to quantify the impact of new energy on power grid. [Method] Construct the evaluation system from multi-dimensional and multi-scale and establish new energy output characteristic index, electric quantity characteristic index, peak regulation characteristic index and flexibility demand index to analyze the new energy output characteristics, the relationship between new energy output and electric quantity, the influence of new energy on peak regulation and the influence of new energy fluctuation on power grid at critical moments. Typical scene features were mined by applying indexes from different time scales such as year, season, month, day and hour. [Result] All kinds of indexes of the evaluation system has been calculated by taking the actual wind power, PV power and load in a certain area as an example. The results show quantitatively the influence of regional new energy on power grid and its distribution characteristics at different time scales. The engineering practicability of the proposed index system is verified. [Conclusion] The proposed index calculation method is quick and simple and the physical meaning of indexes is clear and intuitive and helpful to guide the planning and dispatching of new energy

New insights into the cortex-to-stele ratio show it to effectively indicate inter- and intraspecific function in the absorptive roots of temperate trees

The cortex-to-stele ratio (CSR), as it increases from thin- to thick-root species in angiosperms, is theorised to effectively reflect a compensation for the ‘lag’ of absorption behind transportation. But it is still not known if this compensatory effect exists in gymnosperm species or governs root structure and function within species. Here, anatomical, morphological, and tissue chemical traits of absorptive roots were measured in three temperate angiosperm and three gymnosperm species. Differences in the CSR and the above functional traits, as well as their intraspecific associations, were analyzed and then compared between angiosperms and gymnosperms. At the intraspecific level, the CSR decreased with increasing root order for all species. The expected functional indication of the CSR was consistent with decreases in specific root length (SRL) and N concentration and increases in the C to N ratio (C:N ratio) and the number of and total cross-sectional area of conduits with increasing root order, demonstrating that the CSR indicates the strength of absorption and transportation at the intraspecific level, but intraspecific changes are due to root development rather than the compensatory effect. These trends resulted in significant intraspecific associations between the CSR and SRL (R2 = 0.36 ~ 0.80), N concentration (R2 = 0.48 ~ 0.93), the C:N ratio (R2 = 0.47 ~ 0.91), and the number of (R2 = 0.21 ~ 0.78) and total cross-sectional area (R2 = 0.29 ~ 0.72) of conduits in each species (p< 0.05). The overall mean CSR of absorptive roots in angiosperms was four times greater than in gymnosperms, and in angiosperms, the CSR was significantly higher in thick- than in thin-rooted species, whereas in gymnosperms, the interspecific differences were not significant (p > 0.05). This suggests that the compensation for the lag of absorption via cortex thickness regulation was stronger in three angiosperm species than in three gymnosperm species. In addition, there was poor concordance between angiosperms and gymnosperms in the relationships between CSRs and anatomical, morphological, and tissue chemical traits. However, these gymnosperm species show a more stable intraspecific functional association compared to three angiosperm species. In general, absorptive root CSRs could manifest complex strategies in resource acquisition for trees at both intra- and interspecific levels

The Influence of Agricultural Production Mechanization on Grain Production Capacity and Efficiency

As an important production factor of grain production, agricultural machinery can effectively provide a theoretical basis for agricultural modernization development strategies by exploring its impact on grain production capacity and efficiency. This research starts from the two aspects of grain production capacity and grain production efficiency, takes rice, wheat, and corn as the research objects, and uses the C–D production function and Tobit model as the basis, respectively, to establish two impact models of production capacity and production efficiency. At the same time, according to the different emphases of the two models, this research designs different variable systems and finally uses the data from 2017 to 2021 for empirical analysis. The research results show that the influence coefficients of machinery service income and machinery power resource input on the total grain production capacity are 0.0976 and 0.0437, respectively, with a significant positive impact. At the same time, for rice crops, wheat crops, and corn crops, the amount of mechanization cost per mu has a significant positive impact on the yield capacity of crops, with impact coefficients of 0.0311, 0.0827, and 0.0233, respectively. The supply level of agricultural machinery services and the utilization rate of agricultural machinery services per mu have a significant positive impact on grain production efficiency. The impact coefficients of the supply level of agricultural machinery services per mu are 0.0192, 0.0587, and 0.0241, respectively. The impact coefficients of the agricultural machinery service utilization rate are 0.0059, 0.0148, and 0.0607, respectively, with a significant positive impact. It can be seen that agricultural production mechanization can effectively promote the improvement in grain production capacity and efficiency and promote the process of agricultural modernization. At present, most of the research on industrial mechanization services is biased toward the choice of agricultural mechanization services by farmers. However, this research has carried out the impact mechanism analysis from the perspective of time and space and the perspective of crops, rationalizing the impact mechanism of agricultural production capacity and agricultural production efficiency under agricultural mechanization

A New Error Analysis and Accuracy Synthesis Method for Shoe Last Machine

Abstract: In order to improve the manufacturing precision of the shoe last machine, a new error-computing model has been put forward to. At first, Based on the special topological structure of the shoe last machine and multi-rigid body system theory, a spatial error-calculating model of the system was built; Then, the law of error distributing in the whole work space was discussed, and the maximum error position of the system was found; At last, The sensitivities of error parameters were analyzed at the maximum position and the accuracy synthesis was conducted by using Monte Carlo method. Considering the error sensitivities analysis, the accuracy of the main parts was distributed. Results show that the probability of the maximal volume error less than 0.05 mm of the new scheme was improved from 0.6592 to 0.7021 than the probability of the old scheme,the precision of the system was improved obviously, the model can be used for the error analysis and accuracy synthesis of the complex multi-embranchment motion chain system, and to improve the system precision of manufacturing. Copyright © 2014 IFSA Publishing, S. L

Families of integral trees with diameters 4, 6 and 8

In this paper, some new families of integral trees with diameters 4, 6 and 8 are given. All these classes are infinite. They are different from those in the existing literature. We also prove that the problem of finding integral trees of diameters 4, 6 and 8 is equivalent to the problem of solving Pell’s diophantine equations. The discovery of these integral trees is a new contribution to the search for such trees. I

Construction of a Risk Prediction Model for Postpartum Stress Urinary Incontinence Based on Machine Learning

Pregnancy pregnancy and childbirth is one of the main causes of Stress Urinary Incontinence (SUI). SUI not only affects women's physical health, but also affects women's mental health. 48 puerperae with SUI 6-8 weeks postpartum and 118 puerperae without urinary incontinence during the same period were selected in a hospital in eastern China. Patient information was retrieved from medical records, and postpartum women were asked to complete the International Urinary Incontinence Counseling Questionnaire Short Form (ICI-Q-SF). The early prediction model of SUI was constructed based on the random forest ensemble learning method. Compared with the results of the traditional logistic regression model, the random forest model has better prediction performance and can be used as a screening tool for high-risk groups of SUI during pregnancy to guide clinical work

Study on Heat and Mass Transfer Performance of Ultra-Thin Micro-Heat Pipes

With increased heat control requirements for high-heat-flux products in a narrow heat dissipation space, the ultra-thin micro-heat pipe (MHP) with high heat transfer performance has become an ideal heat dissipation component. In this study, the computational fluid dynamics (CFD) method is used to conduct three-dimensional modeling based on the geometric structure characteristics of an ultra-thin MHP. The capillary pressure of the sintered wick is represented by the modified parameter, and a simple and valuable heat and mass transfer model of the ultra-thin MHP is established by fitting the real experimental data through parameter modification. The flow situation of the working medium inside the ultra-thin MHP is analyzed based on the abovementioned parameters. The results show that when the modified parameter is α = 1.5, the temperature equalization requirements of the ultra-thin MHP can be met to the best degree. Moreover, with an increase in heating power, the error value between the surface temperature data of the model and the experimental data of the ultra-thin MHP sample decreases. Under different heating powers, the working medium inside the ultra-thin MHP has the same flow trend. In addition, a 40% increase in temperature difference is found at the junction of the heating section and the adiabatic section, leading to a fluctuation in the temperature gradient on the heat pipe surface. The research results provide a theoretical basis for the model establishment, heat and mass transfer performance investigation, and parameter optimization of ultra-thin MHPs

City Health Examination and Evaluation of Territory Spatial Planning for SDG11 in China: A Case Study of Xining City in Qinghai Province

City health examination and evaluation of territorial spatial planning is a new policy tool in China. However, research on city health examination and evaluation of territorial spatial planning is still in the exploratory stage in China. Guided by sustainable cities and communities (SDG11), a reasonable city health examination and evaluation index system for Xining City in Qinghai Province is constructed in this paper. The improved technique for order preference by similarity to ideal solution (TOPSIS) was used to quantify the evaluation results, and the city health index was visualized using the city health examination signals and warning panel. The results show that the city health index of Xining City continuously rose from 35.76 in 2018 to 69.76 in 2020. However, it is still necessary to address the shortcomings in innovation, coordination, openness and sharing and to improve the level of city space governance in a holistic way. This study is an exploration of the methodology used in city health examination and the evaluation of territorial spatial planning in China, which can provide a foundation for the sustainable development of Xining City and also provide a case reference for other cities seeking to carry out city health examinations and evaluations of territorial spatial planning in China