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In order to investigate the effects of brassinolide (BR) on the ecological stoichiometric characteristics and internal stability of plants in slope ecological protection under different drought conditions, the biomass, proline content, nutrient content, and internal stability of tall fescue (Festuca arundinacea) in three stress periods were analyzed by weighing water control method, with three drought degrees (75% ± 5%), mild drought (55% ± 5%) and severe drought (35% ± 5%) and four BR concentrations (0 mg/L, 0.05 mg/L, 0.2 mg/L and 0.5 mg/L). The results showed that drought stress resulted in a decrease in plant biomass and nutrient content, and there were differences in carbon, nitrogen and phosphorus contents and their stoichiometric ratios in different organs. Spraying suitable concentration of BR could alleviate plant nutrient loss and promote nutrient accumulation of the tall fescue. Under normal water spraying conditions 0.2 mg/L, under mild and severe drought conditions with spraying of 0.5 mg/L BR, it is most suitable for the nutrient accumulation in tall fescue. The tall fescue showed high sensitivity to exogenous BR input, and the internal stability of the underground part of the tall fescue increased clearly. BR is propitious to the synthesis of proline and enhances the drought resistance of plants. According to stoichiometric characteristics, BR can improve the nitrogen and phosphorus utilization efficiency of tall fescue to a certain extent, and the results of the nitrogen and phosphorus ratio show that nitrogen is the main factor limiting plant growth in a vegetation concrete ecological restoration system, which can supplement nitrogen to accelerate the process of vegetation restoration. The application of BR can improve the biomass and stress resistance of tall fescue, adjust the nutrient distribution strategy and stoichiometric stability, and alleviate the adverse effects of drought on plants. This study provides new ideas and methods for ecological restoration and vegetation reconstruction in arid areas. [ABSTRACT FROM AUTHOR]

The Arithmetic Optimization Algorithm (AOA) is a meta-heuristic algorithm inspired by mathematical operators, which may stagnate in the face of complex optimization issues. Therefore, the convergence and accuracy are reduced. In this paper, an AOA variant called ASFAOA is proposed by integrating a double-opposite learning mechanism, an adaptive spiral search strategy, an offset distribution estimation strategy, and a modified cosine acceleration function formula into the original AOA, aiming to improve the local exploitation and global exploration capability of the original AOA. In the proposed ASFAOA, a dual-opposite learning strategy is utilized to enhance population diversity by searching the problem space a lot better. The spiral search strategy of the tuna swarm optimization is introduced into the addition and subtraction strategy of AOA to enhance the AOA's ability to jump out of the local optimum. An offset distribution estimation strategy is employed to effectively utilize the dominant population information for guiding the correct individual evolution. In addition, an adaptive cosine acceleration function is proposed to perform a better balance between the exploitation and exploration capabilities of the AOA. To demonstrate the superiority of the proposed ASFAOA, two experiments are conducted using existing state-of-the-art algorithms. First, The CEC 2017 benchmark function was applied with the aim of evaluating the performance of ASFAOA on the test function through mean analysis, convergence analysis, stability analysis, Wilcoxon signed rank test, and Friedman's test. The proposed ASFAOA is then utilized to solve the wireless sensor coverage problem and its performance is illustrated by two sets of coverage problems with different dimensions. The results and discussion show that ASFAOA outperforms the original AOA and other comparison algorithms. Therefore, ASFAOA is considered as a useful technique for practical optimization problems. [ABSTRACT FROM AUTHOR]

Against the backdrop of China's growing environmental concerns, investing in green technology innovation is a crucial solution to achieve the goal of "carbon peak and carbon neutrality". Combining the perspectives of signaling theory and corporate governance theory, we use a sample of Chinese-listed companies from 2008 to 2020 to investigate the influence of analysts' green coverage (AGC) on corporate green innovation (CGI) and the moderating effect of corporate environmental information disclosure (CEID) based on a textual analysis approach. The results show that AGC can significantly promote the quantity and quality of CGI, and CEID has a positive moderating effect on the process. Moreover, the mechanism analysis reveals that enhancing investors' value recognition, improving corporate reputation capital, alleviating corporate financing constraints, reducing management agency costs, and curbing managerial myopia are the influence mechanisms of AGC on CGI. Additionally, the positive effect of AGC is more significant for firms located in regions with a favorable institutional environment, firms belonging to heavily polluting industries, and firms that have not adopted continuous innovation strategies. [ABSTRACT FROM AUTHOR]

Based on vegetation-soil nutrient monitoring data under different precipitation conditions, this study investigated the impact of precipitation changes on the ecological restoration process of disturbed slopes. Precipitation change, to a certain extent, changed the carbon (C), nitrogen (N) and phosphorus (P) content and the stoichiometric ratio of the soil–plant system. With the increase of the weekly precipitation from 10 to 20 mm, the C content of Cynodon and Indigofera Amblyantha Craib on each slope gradually increased, increased by 8.69% and 4.28%, respectively, compared with the initial recovery period, and the N/P of Cynodon increased from 3.81 to 4.94, and the N limit gradually decreased, while the limit of P increased continuously. The efficiency of the coordinated utilization of N and P of the Indigofera Amblyantha Craib increased, which had a certain adaptability to changes in precipitation. The C/N and C/P in the soil first increased and then decreased, and reached the peak at the slope of 15 mm precipitation, while the N/P fluctuated around 0.35 overall. N was an important element restricting the growth of grass, while P was an important influencing element limiting the growth of shrubs. This also showed that soil C, N and P had a good promoting effect on plant growth, and the self-regulating nutrient utilization strategies of different growth forms of plants under different precipitation conditions differed. There was a coupling effect in the contents of C, N, P and their stoichiometric ratio in the soil–plant system, and stoichiometry and elastic ecological interactions jointly controlled the supply and demand of elements in the plants, but there was no consistent temporal pattern of nutrient ecological stoichiometric ratio in the plant–soil system during the recovery process, thus requiring further research and evaluation. [ABSTRACT FROM AUTHOR]

To obtain a crumb rubber asphalt mixture with excellent performance, this study combined trans-polyoctenamer rubber (TOR), crumb rubber, and other additives to establish a new type of crumb rubber (CRT). The objective of this study was to design and evaluate the road performance of the new type of crumb rubber asphalt mixture (CRTAM) with a skeleton dense texture through a dry process. First, the skeleton intrusion compact volume method was used to optimize the grading of coarse and fine aggregates, and the design of the CRTAM gradation was carried out through the same and unequal volume replacement grading method. Then, three types of road performance were analyzed: high-temperature stability, low-temperature crack resistance, and water stability. The results showed that 2% and 2.5% CRT met a low-temperature index with equal volume substitution, and the six gradations obtained by unequal volume replacement with 2% CRT complied with the requirements of a skeleton dense texture. When the substitution ratio was 1.5 and 0.5, the high-temperature performance was better. In addition, when the substitution ratio was 0.5, the flexural strain energy density was the highest and the low-temperature performance was the best. Including considerations of economic benefits, it is recommended that the CRT content be 2% and the substitution ratio be 0.5. [ABSTRACT FROM AUTHOR]

As a renewable biomass resource, biochar is new to modify or replace asphalt binder in pavement engineering. This paper focuses on the effect of biochar on the anti-aging performance of asphalt binder. The short- and long-term aging properties of biochar modified asphalt binder were investigated using dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests. The modification mechanism was investigated through the Fourier-transform infrared spectroscopy (FTIR) test. The aging tests and viscosity analysis showed that the softening point of biochar modified asphalt binder was higher than base asphalt binder, while the aging index and aging viscosity ratio were lower than base asphalt binder. After aging, the temperature sensitivity of biochar modified asphalt binder decreased and the high-temperature stability, reflected by dynamic shear modulus and resistance to rutting, improved. The BBR test after long-term aging showed that the anti-aging performance of biochar modified asphalt binder decreased with the decrease in temperature, and control of the biochar content could ensure good low-temperature performance of the modified asphalt binder after aging. FTIR spectra analysis showed that biochar in modified asphalt binder is physically blended with asphalt binder. [ABSTRACT FROM AUTHOR]

The dynamic stability of a rutting test does not optimally reflect the high-temperature stability of asphalt mixtures. In this study, a rutting test was performed over a long duration (4 h) at different temperatures (40, 50, 60, 70 °C) for three asphalt mixtures, namely, matrix AC-16, SMA-16, and modified AC-16 asphalt mixtures. Subsequently, the temperature rutting rate was obtained after considering the annual temperature conditions of Guangdong and Beijing in China. Because the conditions of the rutting test were different from that of the actual pavement, the rut depth was calculated using a modified temperature rutting rate. This modification considered four factors: wheel trace distribution, temperature, pavement thickness, and loading rate. The calculation of the temperature rutting rate considered the climatic conditions and utilized the rutting deformation data from hour 1–4 of the rutting tests, during which the asphalt mixture was in a stable creep period. Thus, the high-temperature stability of the asphalt mixture was reflected more scientifically by the temperature rutting rate than the dynamic stability. The high-temperature rut-resistance of the asphalt mixture was found to improve significantly after the introduction of two additives (anti-rutting agent and lignin fiber). The modified formula for rut depth can realistically predict the annual rutting depth for three asphalt mixtures in a one-way driving pavement. [ABSTRACT FROM AUTHOR]

Monitoring the performance of hybrid rice seeding is very important for the seedling production line to adjust the sowing amount of the seeding device. The objective of this paper was to develop a system for the real-time online monitoring of the performance of hybrid rice seeding based on embedded machine vision and machine learning technology. The embedded detection system captured images of pot trays that passed under the illuminant cabinet installed in the seedling production line. This paper proposed an algorithm for fixed threshold segmentation by analyzing the images with the exploratory analysis method. With the algorithm, the grid image and seed image were extracted from the pot tray image. The paper also proposed a method for obtaining pixel coordinates of gridlines from the grid image. Binary images of seeds were divided into small pieces, according to the pixel coordinates of gridlines. Each piece corresponded to a cell on the pot tray. By scanning the contours in each piece of the image to check whether there were seeds in the cell, the number of empty cells was counted and then used to calculate the missing rate of hybrid rice seeding. The seed number sowed in pot trays was monitored while using the machine learning approach. The experimental results demonstrated that it would consume 4.863 s for the device to process an image, which allowed for the detection of the missing rate and seed number in real-time at the rate of 500 trays per hour (7.2 s per tray). The average accuracy of the detection of missing rates of a seedling production line was 94.67%. The average accuracy of the detection of seed numbers was 95.68%. [ABSTRACT FROM AUTHOR]