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In this study, a spiral bevel gearbox of the aero-engine is taken as the research object. A method of gear system-level modal analysis of bevel gears is proposed. Based on the design parameters and machining parameters, a 3D model of spiral bevel gear pairs with accurate tooth surface is established. Then the static analysis of the gear pair is carried out to determine the normal contact of the gears. After that, the pre-stressed modal analysis is done to obtain the modal of the gear system. And the result is compared with the experimental data to verify the accuracy and effectiveness of the method. Finally, according to the engineering practice, the influence of different contact surfaces and loads on the system mode is analyzed. The results show that the pre-stressed modal analysis method based on accurate tooth surface can be used for modal analysis of the bevel gear system. The system mode has strong sensitivity to the contact surfaces but is weak to loads. That is to say, in a certain range, the influence of loads can be ignored, but the modal analysis of different contact surfaces is needed.

The original version of this Article omitted a reference to previous work in Stojanovic, M. N. & Stefanovic, D. A deoxyribozyme-based molecular automaton. Nat. Biotechnol. 21, 1069-1074 (2003). This has been added as reference 42. The following has been added after the third sentence of the fifth paragraph of the Discussion: Integration could also allow more sophisticated information processing, for example as shown by the classic deoxyribozyme-based automaton that plays tic-tac-toe42, to direct structural reconfiguration (Supplementary Discussion). This has been corrected in the PDF and HTML versions of the Article.

The dynamic interactions between complex molecular structures underlie a wide range of sophisticated behaviors in biological systems. In building artificial molecular machines out of DNA, an outstanding challenge is to develop mechanisms that can control the kinetics of interacting DNA nanostructures and that can compose the interactions together to carry out system-level functions. Here we show a mechanism of DNA tile displacement that follows the principles of toehold binding and branch migration similar to DNA strand displacement, but occurs at a larger scale between interacting DNA origami structures. Utilizing this mechanism, we show controlled reaction kinetics over five orders of magnitude and programmed cascades of reactions in multi-structure systems. Furthermore, we demonstrate the generality of tile displacement for occurring at any location in an array in any order, illustrated as a tic-tac-toe game. Our results suggest that tile displacement is a simple-yet-powerful mechanism that opens up the possibility for complex structural components in artificial molecular machines to undergo information-based reconfiguration in response to their environments.

Near-space high-altitude balloon-based platforms have a series of advantages and provide superior conditions for optical observation. In order to ensure the stability of the optical axis of the optical detection load and stable tracking of the target, a near-space high-altitude balloon-based high-precision pointing and tracking system was designed, which can compensate for changes in the pitch angle and azimuth angle of the platform during flight. The system includes a primary platform stable pointing system and a secondary precise tracking system. In the finished flight experiment, the primary platform pointing system and secondary precise tracking system on the balloon-based observation platform worked normally, providing a guarantee for the coronagraph's stable tracking and detection of the sun. The primary platform pointing system can realize ±1° pointing accuracy, and the simulated accuracy of the secondary precise tracking system is 4″, which guaranteed that the coronagraph obtained more than 20,000 images. In subsequent works, we will upgrade and optimize the whole system and conduct our next flight experiment in the future. [ABSTRACT FROM AUTHOR]

In order to improve the control of a moving mirror control system and enhance the anti-interference ability of the system, active disturbance rejection control (ADRC) with parameter autotuning is proposed and applied to control a rotary voice coil motor (RVCM). Improved snake optimization (I-SO) was applied to tune and optimize ADRC's key parameters. To obtain excellent parameters efficiently, in the population initialization phase of SO, the quality and diversity of initial solutions were improved through a chaotic elite opposition learning algorithm. In the local search phase, a sine and cosine (SC) search mode was introduced to enhance the local search ability of SO. The simulation results show that I-SO can effectively find the ideal parameters. I-SO has excellent search capability and stability. The experimental control system of a moving mirror was established, and the effectiveness of the parameters optimized by I-SO was verified. ADRC with parameter autotuning showed excellent control in the moving mirror control system, and the stability of the optical path scanning speed reached 99.2%. [ABSTRACT FROM AUTHOR]

From bacteria following simple chemical gradients.sup.1 to the brain distinguishing complex odour information.sup.2, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks.sup.3, but has been limited to the recognition of a set of no more than four patterns, each composed of four distinct DNA molecules. Winner-take-all computation.sup.4 has been suggested.sup.5,6 as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits.sup.7 and Hopfield networks.sup.8 used previously.sup.3, winner-take-all circuits are computationally more powerful.sup.4, allow simpler molecular implementation and are not constrained by the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement.sup.9,10 reactions. We use a previously developed seesaw DNA gate motif.sup.3,11,12, extended to include a simple and robust component that facilitates the cooperative hybridization.sup.13 that is involved in the process of selecting a 'winner'. We show that with this extended seesaw motif DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10 × 10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits '1' to '9'. The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns 'remembered' during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory.DNA-strand-displacement reactions are used to implement a neural network that can distinguish complex and noisy molecular patterns from a set of nine possibilities--an improvement on previous demonstrations that distinguished only four simple patterns., Author(s): Kevin M. Cherry [sup.1] , Lulu Qian [sup.1] [sup.2] Author Affiliations:(1) Bioengineering, California Institute of Technology, Pasadena, USA(2) Computer Science, California Institute of Technology, Pasadena, USAMain Winner-take-all computation[sup.4] is [...]

Author(s): Grigory Tikhomirov [1]; Philip Petersen [2]; Lulu Qian (corresponding author) [1, 3] Self-assembled DNA nanostructures [1] enable nanometre-precise patterning that can be used to create programmable molecular machines [2, [...]

The principle of the NC planing process of the spur face-gear is briefly introduced,the equations of the tooth profile and the tooth cutter are derived,the mathematical relation between the tooth cutter angle and the allowance is established,and then,the machining path of the NC planing of the spur face-gear is optimized. With the comparison result between the optimized machining path and the previous one,it is indicated that the proposed optimized method can shorten the feeding times by 50%. Finally,the optimized machining path is simulated in NC codes with the Vericut software,which shows that the optimized machining path method for the NC planing of the spur face-gear is feasible,efficient and can meet the precision requirement.

The impressive capabilities of the mammalian brain--ranging from perception, pattern recognition and memory formation to decision making and motor activity control--have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control (1). Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the 'intelligent' behaviour required for survival (2). However, the study of how molecules can 'think' has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo (3,2,4) and the synthesis of artificial chemical analogues has been proposed theoretically (5-9), experimental work (10-13) has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing (14) and strand displacement circuitry (15), we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture (16) that allows experimental scale-up of multilayer digital circuits (17), we systematically transform arbitrary linear threshold circuits (18) (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory (19) with four fully connected artificial neurons that, after training insilico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment., The human brain is composed of ~[10.sup.11] neurons, and each has a few thousand synapses. Each synapse can receive signals from other neurons, raising or lowering the electrical potential inside [...]