Generating pseudorandom numbers with good statistical performance based on chaotic maps has become a topic of interest in chaotic cryptography. Several high-order polynomial chaotic maps with special ...forms are proposed by the Li–Yorke theorem in this paper, and chaotic conditions and intervals are given. The dynamical behaviors of chaotic maps satisfying the chaotic conditions are numerically analyzed, such as the bifurcation and Lyapunov exponent, the analysis results show the correctness of the related chaos criterion theorems. Chaotic maps are essential for the design of pseudorandom number generator and are widely used in many applications. Based on the superposition of chaotic maps, a pseudorandom number generator is designed, and the available chaotic parameters of the pseudorandom number generator are increased through the superposition of chaotic maps. This paper tests and analyses the performance of pseudorandom sequences produced by the pseudorandom number generator, and the analysis results show that pseudorandom sequences produced by pseudorandom number generator have good randomness, uniformity, complexity, and sensitivity to the initial parameters. Performance analyses show that the pseudorandom number generator in this paper can generate sequences with high quality. Several high-order polynomial chaotic maps we constructed based on the Li–Yorke theorem enrich the chaotic map and provide the possibility for its application in the field of cryptography.
Abstract
The electronic and topological properties of MoS
2
monolayers with n-p codoping effect are investigated by using first-principles calculations. Two types of the doped Nb atoms play the roles ...of the p-type and n-type dopants, respectively. The n-p codoping is found inducing a large valley polarization, associated with the strong magnetization induced by the Nb dopants. Interestingly, the system simultaneously owns a perfect Chern insulating band gap opened exactly at the Fermi level. The nontrivial band gap comes from the lifting of the degeneracy of the d
xz
and d
yz
orbitals of Nb
2
atoms after the spin-orbit coupling is considered. Our work inspires exciting prospects to tune the novel properties of materials with n-p codoping effects.
The modeling and compensation method is a common method for reducing the influence of thermal error on the accuracy of machine tools. The prediction accuracy and robustness of the thermal error model ...are two key performance measures for evaluating the compensation effect. However, it is difficult to maintain the prediction accuracy and robustness at the desired level when the ambient temperature exhibits strong seasonal variations. Therefore, a year-round thermal error modeling and compensation method for the spindle of machine tools based on ambient temperature intervals (ATIs) is proposed in this paper. First, the ATIs applicable to the thermal error prediction models (TEPMs) under different ambient temperatures are investigated, where the C-Means clustering algorithm is utilized to determine ATIs. Furthermore, the prediction effect of different numbers of ATIs is analyzed to obtain the optimal number of ATIs. Then, the TEPMs corresponding to different ATIs in the annual ambient temperature range are established. Finally, the established TEPMs of ATIs are used to predict the experimental data of the entire year, and the prediction accuracy and robustness of the proposed ATI model are analyzed and compared with those of the low and high ambient temperature models. The prediction accuracies of the ATI model are 20.6% and 41.7% higher than those of the low and high ambient temperature models, respectively, and the robustness is improved by 48.8% and 62.0%, respectively. This indicates that the proposed ATI method can achieve high prediction accuracy and robustness regardless of the seasonal temperature variations throughout the year.
Chatter has been playing an important role in the stability and quality assurance of milling processes. To effectively predict the stability of milling processes, in this paper, we investigate ...multiple milling parameters, including the spindle speed, axial milling depth, radial milling width, milling cutter radius, chip thickness, and feed rate. The influence mechanism of these parameters on milling stability is analyzed systematically. Based on the analysis results, three-dimensional (3D) stability lobe diagrams (SLDs) under multiple milling parameters can be obtained, which provide a theoretical basis of preventing and suppressing chatter. The effectiveness of the SLDs is verified by the actual milling experiment. Compared with the traditional two-dimensional SLDs, the proposed 3D SLDs with multiple parameters are more comprehensive, accurate and practical, which show important theoretical significance and engineering application value for the chatter stability prediction and control.
Halogens are among the most electronegative elements, and the variations in size and polarizability of halogens require different descriptions of the intermolecular bonds they form. Here we use the ...inelastic tunneling probe (itProbe) to acquire real-space imaging of intermolecular-bonding structures in the two-dimensional self-assembly of halogenbenzene molecules on a metal surface. Direct visualization is obtained for the intermolecular attraction and the “windmill” pattern of bonding among the fully halogenated molecules. Our results provide a hitherto missing understanding of the nature of the halogen bond.
Establishing a mathematical model to predict and compensate for the thermal error of CNC machine tools is a commonly used approach. Most existing methods, especially those based on deep learning ...algorithms, have complicated models that need huge amounts of training data and lack interpretability. Therefore, this paper proposes a regularized regression algorithm for thermal error modeling, which has a simple structure that can be easily implemented in practice and has good interpretability. In addition, automatic temperature-sensitive variable selection is realized. Specifically, the least absolute regression method combined with two regularization techniques is used to establish the thermal error prediction model. The prediction effects are compared with state-of-the-art algorithms, including deep-learning-based algorithms. Comparison of the results shows that the proposed method has the best prediction accuracy and robustness. Finally, compensation experiments with the established model are conducted and prove the effectiveness of the proposed modeling method.
The loading of dissolved organic carbon (DOC) from soils to inland waters and ultimate transport to the ocean is a critical flux pathway in the terrestrial biosphere carbon cycle. Fires can ...significantly affect this flux through biogeochemical processes related to oxidation and mobilization of DOC in the soil. Therefore, in order to accurately estimate and model terrestrial carbon storage and export to the marine environment, we need to better understand the effects of fire on DOC flux. In this analysis, we compiled available observational data sets from seven watersheds across the conterminous United States generally spanning the years 1999-2019. We used these data sets to examine the effects of fire on riverine DOC concentration draining a watershed to study both the immediate impacts and the post-fire recovery patterns. Our results suggest that these fires result in an immediate decrease in riverine DOC concentration draining the watershed by 26 ± 15%, and the time required for DOC concentrations to recover to pre-fire levels was estimated to be, on average, approximately 9 months. During recovery, DOC concentration was 24 ± 11% lower than the long-term average for the watershed. In addition, the larger the proportion of the watershed that burned, the greater the concentration decrease and the longer the time period for post-fire recovery.
The conventional thermal error compensation for computer numerical control machine tools in ISO 230-3:2007 is based on a single positioned point on a worktable; this guideline ignores the thermal ...error differences of different locations across an entire worktable. As a result, a reduced compensation effect is achieved for the whole worktable, although the single-point compensation model generally provides high prediction accuracy. The 2D thermal error compensation method, which can greatly improve the compensation effect of the worktable, is proposed in this study. This method builds a 2D thermal error map model parallel to the worktable at each time point. The thermal error at any position on the workbench can be predicted accurately. Thus, this compensation method can significantly reduce the influence of thermal error differences on the compensation effect across the whole worktable. The thermal error prediction results and compensated experimental results show that the compensation effect of this new method is better than that of the conventional single-point method for the whole worktable.
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•Climate zone shifts of northeastern US and maritime Canada delineated and characterized.•Based on differing spatial resolutions, optimal zones of 3, 9, 15, and 21 were ...determined.•Current high diversity of distinct climate zones in region is anticipated to decrease.•Projected shifts have important implications for regional forest structure and productivity.
Climate zones play a significant role in shaping the forest ecosystems located within them by influencing multiple ecological processes, including growth, disturbances, and species interactions. Therefore, delineation of current and future climate zones is essential to establish a framework for understanding and predicting shifts in forest ecosystems. In this study, we developed and applied an efficient approach to delineate regional climate zones in the northeastern United States and maritime Canada, aiming to characterize potential shifts in climate zones and discuss associated changes in forest ecosystems. The approach comprised five steps: climate data dimensionality reduction, sampling scenario design, cluster generation, climate zone delineation, and zone shift prediction. The climate zones in the study area were delineated into four different orders, with increasing subzone resolutions of 3, 9, 15, and 21. Furthermore, projected climate normals under Shared Socioeconomic Pathways 4.5 and 8.5 scenarios were used to predict the shifts in climate zones until 2100. Our findings indicate that climate zones characterized by higher temperatures and lower precipitation are expected to become more prevalent, potentially becoming the dominant climate condition across the entire region. Thes changes are likely to alter regional forest composition, structure, and productivity. In short, such shifts in climate underscore the significant impact of environmental change on forest ecosystem dynamics and carbon sequestration potential.
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•EGSB treatment of food waste could tolerate a fluctuation of COD.•Dissolved ammonia nitrogen and organic nitrogen were mainly removed.•Methanothrix were the predominant ...archaea.•Amino acids metabolism decreased and energy metabolism increased at high OLR.
The influent and effluent nitrogen compositions of an expanded granular sludge blanket (EGSB) reactor employed for treating food waste (FW) operated under ambient temperature was evaluated. Additionally, dynamic changes in the bacterial community structures and its metabolic functions were investigated. Results show that the EGSB reactor had a good effect on FW disposal and well resistance to variations in the organic loading rate. Furthermore, the COD concentration in the influent increased to about 10,000 mg/L and the COD removal rate stabilized at about 95%. The dissolved ammonia nitrogen (d-ammonia) content was the largest, accounting for approximately 70–80% of the dissolved nitrogen in the effluent. The amount of particulate organic nitrogen (PON) decreased by about 25%–33%. Amino acid, carbohydrate and lipid metabolism decreased at high organic loading rate (OLR). Meanwhile, the abundance of Methanothrix increased from 30.82% to 70.25%, whereas Methanobacterium decreased from 66.14% to 14.49%.
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