Fourier convolution-parallel neural network framework with library matching for multi-tool processing decision-making in optical fabrication.

Intelligent manufacturing of ultra-precision optical surfaces is urgently desired but rather difficult to achieve due to the complex physical interactions involved. The development of data-oriented neural networks provides a new pathway, but existing networks cannot be adapted for optical fabrication with a high number of feature dimensions and a small specific dataset. In this Letter, for the first time to the best of our knowledge, a novel Fourier convolution-parallel neural network (FCPNN) framework with library matching was proposed to realize multi-tool processing decision-making, including basically all combination processing parameters (tool size and material, slurry type and removal rate). The number of feature dimensions required to achieve supervised learning with a hundred-level dataset is reduced by 3-5 orders of magnitude. Under the guidance of the proposed network model, a 260 mm × 260 mm off-axis parabolic (OAP) fused silica mirror successfully achieved error convergence after a multi-process involving grinding, figuring, and smoothing. The peak valley (PV) of the form error for the OAP fused silica mirror decreased from 15.153λ to 0.42λ and the root mean square (RMS) decreased from 2.944λ to 0.064λ in only 25.34 hours. This network framework has the potential to push the intelligence level of optical manufacturing to a new extreme.

Modeling and in-depth analysis of the mid-spatial-frequency error influenced by actual contact pressure distribution in sub-aperture polishing.

In ultra-precision optical processing, the sub-aperture polishing is prone to produce a mid-spatial-frequency (MSF) error. However, the generation mechanism of the MSF error is still not fully clarified, which seriously affects the further improvement of optical component performance. In this paper, it is proved that the actual contact pressure distribution between the workpiece and tool is a crucial source which affects the MSF error characteristics. A rotational periodic convolution (RPC) model is proposed to reveal the quantitative relationship among the contact pressure distribution, speed ratio (spin velocity/feed speed) and MSF error distribution. In-depth analyses show that the MSF error is linearly related to the symmetry level of contact pressure distribution and inversely proportional to the speed ratio, where the symmetry level is effectively evaluated by the proposed method based on Zernike polynomials. In the experiments, according to the actual contact pressure distribution obtained from the pressure-sensitive paper, the error rate of modeling results under different processing conditions is around 15%, which proves the validity of the proposed model. The influence of contact pressure distribution on the MSF error is further clarified through the establishment of RPC model, which can further promote the development of sub-aperture polishing.

Statistical perception of the chaotic fabrication error and the self-adaptive processing decision in ultra-precision optical polishing.

Subaperture polishing is a key technique for fabricating ultra-precision optics. However, the error source complexity in the polishing process creates large fabrication errors with chaotic characteristics that are difficult to predict using physical modelling. In this study, we first proved that the chaotic error is statistically predictable and developed a statistical chaotic-error perception (SCP) model. We confirmed that the coupling between the randomness characteristics of chaotic error (expectation and variance) and the polishing results follows an approximately linear relationship. Accordingly, the convolution fabrication formula based on the Preston equation was improved, and the form error evolution in each polishing cycle for various tools was quantitatively predicted. On this basis, a self-adaptive decision model that considers the chaotic-error influence was developed using the proposed mid- and low-spatial-frequency error criteria, which realises the automatic decision of the tool and processing parameters. An ultra-precision surface with equivalent accuracy can be stably realised via proper tool influence function (TIF) selection and modification, even for low-deterministic level tools. Experimental results indicated that the average prediction error in each convergence cycle was reduced to 6.14%. Without manual participation, the root mean square(RMS) of the surface figure of a ϕ100-mm flat mirror was converged to 1.788 nm with only robotic small-tool polishing, and that of a ϕ300-mm high-gradient ellipsoid mirror was converged to 0.008 λ. Additionally, the polishing efficiency was increased by 30% compared with that of manual polishing. The proposed SCP model offers insights that will help achieve advancement in the subaperture polishing process.

Sinorhizobium meliloti ohrR genes affect symbiotic performance with alfalfa (Medicago sativa).

Sinorhizobium meliloti infects the host plant alfalfa to induce formation of nitrogen-fixation root nodules, which inevitably elicit reactive oxygen species (ROS) bursts and organic peroxide generation. The MarR family regulator OhrR regulates the expression of chloroperoxidase and organic hydrogen resistance protein, which scavenge organic peroxides in free-living S. meliloti cells. The single mutant of ohrR genes SMc01945 (ohrR1) and SMc00098 (ohrR2) lacked symbiotic phenotypes. In this work, we identified the novel ohrR gene SMa2020 (ohrR3) and determined that ohrR genes are important for rhizobial infection, nodulation and nitrogen fixation with alfalfa. By analysing the phenotypes of the single, double and triple deletion mutants of ohrR genes, we demonstrate that ohrR1 and ohrR3 slightly affect rhizobial growth, but ohrR2 and ohrR3 influence cellular resistance to the organic peroxide, tert-butyl hydroperoxide. Deletion of ohrR1 and ohrR3 negatively affected infection thread formation and nodulation, and consequently, plant growth. Correspondingly, the expression of the ROS detoxification genes katA and sodB as well as that of the nitrogenase gene nifH was downregulated in bacteroids of the double and triple deletion mutants, which may underlie the symbiotic defects of these mutants. These findings demonstrate that OhrR proteins play a role in the S. meliloti-alfalfa symbiosis.

Molecular oxygen levels regulate Sinorhizobium meliloti cell division through a FixJ-dependent transcription control mechanism.

Rhizobia infect the roots of host legumes and induce formation of nitrogen-fixing nodules, where nitrogenase genes are inducibly expressed by micro-aerobic signals. FixL/FixJ is an oxygen signal sensing system that is unique to rhizobia. FixL monitors molecular oxygen levels and phosphorylates the response regulator FixJ, thereby regulating downstream gene expression. The cell division of rhizobia is regulated by a phosphorylation relaying cascade that includes the transcription factors CtrA, GcrA, and DnaA. In Sinorhizobium meliloti the expression of these proteins is regulated by NtrX, which affects cell division. In the present work, by analyzing the cell division phenotypes and gene expression patterns of S. meliloti fixJ and ntrX mutants, we found that S. meliloti cell division is regulated by oxygen gas levels. Under normal conditions, FixJ induced NtrX and DnaA expression, but repressed CtrA and GcrA expression. In contrast, under hypoxic conditions, phosphorylated FixJ specifically bound to gene promoter regions to directly induce CtrA and GcrA expression, but to repress DnaA expression. Our findings reveal that molecular oxygen levels regulate S. meliloti cell division by a FixJ-dependent transcription control mechanism.

Inconsistent individual personality description eliminates the other-race effect.

The present study investigated the effect of individual semantic information displayed simultaneously with faces on the other-race effect. Arbitrary descriptions of the individual personalities of a set of faces were initially evaluated for consistency. Later, 83 naïve participants were allocated to three groups in which they saw faces and consistent, inconsistent, or neutral personality information about each face. Later, they completed a recognition task for the faces. The other-race effect was observed only in the control group and the consistent-information group, but not in the inconsistent-information group. This showed that inconsistent individual semantic information for each face can help to individuate these faces and eliminated the other-race effect.