Freeform optical system design with differentiable three-dimensional ray tracing and unsupervised learning.

Optical systems have been crucial for versatile applications such as consumer electronics, remote sensing and biomedical imaging. Designing optical systems has been a highly professional work due to complicated aberration theories and intangible rules-of-thumb, hence neural networks are only coming into this realm until recent years. In this work, we propose and implement a generic, differentiable freeform raytracing module, suitable for off-axis, multiple-surface freeform/aspheric optical systems, paving the way toward a deep learning-based optical design method. The network is trained with minimal prior knowledge, and it can infer numerous optical systems after a one-time training. The presented work unlocks great potential for deep learning in various freeform/aspheric optical systems, and the trained network could serve as an effective, unified platform for generating, recording, and replicating good initial optical designs.

Generalization of learned Fourier-based phase-diversity wavefront sensing.

Proper initialization of the nonlinear optimization is important to avoid local minima in phase diversity wavefront sensing (PDWS). An effective neural network based on low-frequency coefficients in the Fourier domain has proved effective to determine a better estimate of the unknown aberrations. However, the network relies significantly on the training settings, such as imaging object and optical system parameters, resulting in a weak generalization ability. Here we propose a generalized Fourier-based PDWS method by combining an object-independent network with a system-independent image processing procedure. We demonstrate that a network trained with a specific setting can be applied to any image regardless of the actual settings. Experimental results show that a network trained with one setting can be applied to images with four other settings. For 1000 aberrations with RMS wavefront errors bounded within [0.2 λ, 0.4 λ], the mean RMS residual errors are 0.032 λ, 0.039 λ, 0.035 λ, and 0.037 λ, respectively, and 98.9% of the RMS residual errors are less than 0.05 λ.

STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis.

OBJECTIVE: This study was aimed to identify the biomarkers for diagnosis and reveal the immune microenvironment changes in ankylosing spondylitis (AS). METHODS: GSE73754 was downloaded for the co-expression network construction and immune cell analyses. Flow cytometric analysis was performed to validate the results of bioinformatics analysis. Gene set enrichment analysis (GSEA) was performed to investigate the potential biological characteristic between different phenotypes. Pearson correlation analysis between the hub genes and the xCell score of immune cell types was performed. RESULTS: Signal transducer and activator of transcription 3 (STAT3) and Spi-1 proto-oncogene (SPI1) was identified as the hub genes in the datasets GSE73754. And the t-test showed that the expression level of STAT3 and SPI1 in the GSE73754 was significantly higher in AS and human leukocyte antigen (HLA)-B27(+) groups. Flow cytometric analysis showed that natural killer T cells (NKT) cells were upregulated, while Th1 cells were down-regulated in AS, which was consistent with the results obtained from bioinformatics analysis. STAT3 and SPI1 was correlated with the NKT cells and Th1 cells. CONCLUSION: STAT3 and SPI1 may be a key cytokine receptor in disease progression in AS.

Phase-diversity wavefront sensing enhanced by a Fourier-based neural network.

Phase diversity wavefront sensing (PDWS) has been a successful approach to quantifying wavefront aberrations with only a few intensity measurements and nonlinear optimization. However, the inherent non-convexity of the inverse problem may lead to stagnation at a local minimum far from the true solution. Proper initialization of the nonlinear optimization is important to avoid local minima and improve wavefront retrieval accuracy. In this paper, we propose an effective neural network based on low-frequency coefficients in the Fourier domain to determine a better estimate of the unknown aberrations. By virtue of the proposed network, only a small amount of simulation data suffice for a robust training, two orders of magnitude less than those in existing work. Experimental results show that, when compared with some existing methods, our method achieves the highest accuracy while drastically reducing the training time to 1.4 min. The minimum, maximum, and mean values of the root mean square (RMS) residual errors for 800 aberrations are 0.017λ, 0.056λ, and 0.039λ, respectively, and 95% of the RMS residual errors are less than 0.05λ.

Miniaturized cost-effective broadband spectrometer employing a deconvolution reconstruction algorithm for resolution enhancement.

We demonstrate a miniaturized broadband spectrometer employing a reconstruction algorithm for resolution enhancement. We use an opto-digital co-design approach, by firstly designing an optical system with certain residual aberrations and then correcting these aberrations with a digital algorithm. The proposed optical design provides an optical resolution less than 1.7 nm in the VIS-channel (400-790 nm) and less than 3.4 nm in the NIR-channel (760-1520 nm). Tolerance analysis results show that the components are within a commercial class, ensuring a cost-efficient design. We build the prototype with a size of 37x30x26 mm3 and demonstrate that by applying a restoration algorithm, the optical resolution can be further improved to less than 1.3 nm (VIS-channel) and less than 2.3 nm (NIR-channel).

Compact Shortwave Infrared Imaging Spectrometer Based on a Catadioptric Prism.

This article demonstrates a compact prism imaging spectrometer method. A catadioptric curved prism is located at the secondary mirror position of the spectrometer and used to balance the aberrations, enlarge the dispersion width, and decrease the volume. A mathematical model of the prism and spectrometer is derived, which provides an optimal initial structure for a non-coaxial spectrometer, simplifying the optical design process and reducing the system volume. Using this method, a compact shortwave infrared imaging spectrometer with a 16° field of view is designed with an F-number/3, and the measured spectrum ranges from 0.95 to 2.5 µm. The performance is analyzed and evaluated. Laboratory testing results prove the excellent optical performance, and under the same specifications, the spectrometer length decreases by 40%.

Subacute dermal toxicity study of bensulfuron-methyl in Sprague-Dawley rats.

Background: Bensulfuron-methyl has recently attracted attention given its widespread use as an herbicide in crops, especially its transdermal safety. However, no dermal toxicity study of this pesticide to mammals has been reported. The present study aims to investigate subacute dermal toxicity of bensulfuron-methyl following repeated doses exposure.Methods: Forty-eight Sprague-Dawley rats were randomly divided into four groups: a normal control group and bensulfuron-methyl groups of different concentrations (250, 500, 1000 mg/kg.bw/day). The rats were topically applied with the substance dermally for 6 h per day for 28 days. At the end of the experiment, all rats were monitored for any changes in their hematological, biochemical parameters, and pathological and histological sections.Results: There were no statistically significant differences (P ≥ 0.05) in the hematological parameters and biochemical parameters. The pathological histological results of rats in the control and the highest concentration group showed no significant abnormalities. The NOAEL of subacute dermal toxicity study was found to be 1000 mg/kg.bw/day in both female and male rats.Conclusion: The result indicated that bensulfuron-methyl is probably safe for humans as a pesticide.

Automated freeform imaging system design with generalized ray tracing and simultaneous multi-surface analytic calculation.

Recently, freeform optics has been widely used due to its unprecedented compactness and high performance, especially in the reflective designs for broad-wavelength imaging applications. Here, we present a generalized differentiable ray tracing approach suitable for most optical surfaces. The established automated freeform design framework simultaneously calculates multi-surface coefficients with merely the system geometry known, very fast for generating abundant feasible starting points. In addition, we provide a "double-pass surface" strategy with desired overlap (not mutually centered) that enables a component reduction for very compact yet high-performing designs. The effectiveness of the method is firstly demonstrated by designing a wide field-of-view, fast f-number, four-mirror freeform telescope. Another example shows a two-freeform, three-mirror, four-reflection design with high compactness and cost-friendly considerations with a double-pass spherical mirror. The present work provides a robust design scheme for reflective freeform imaging systems in general, and it unlocks a series of new 'double-pass surface' designs for very compact, high-performing freeform imaging systems.

Energy-Efficient Spatial Query-Centric Geographic Routing Protocol in Wireless Sensor Networks.

In data-centric wireless sensor networks (WSNs), sensing data have a high time-space correlation. Most queries are spatial and used to obtain data in a defined region. Geographic routing (GR) protocols are the optimal choice for routing spatial queries. However, several drawbacks still exist in GRs, and these the include premature death of nodes and communication latency, which result in reduced network life and query efficiency. A new clustering GR protocol called quadtree grid (QTGrid) was proposed in this study to save energy and improve spatial query efficiency. First, the monitoring area was logically divided into clusters by a quadtree structure, and each grid's location was encoded to reduce the memory overhead. Second, cluster head (CH) nodes were selected based on several metrics, such as distance from the candidate node to the grid center and adjacent CHs and residual energy. Third, the next-hop routing node was selected depending on the residual energy of the candidate node and its distance to the sink node. Lastly, a lossless data aggregation algorithm and a flexible spatial query algorithm were adopted to reduce the transmission of redundant data and meet the application requirements, respectively. Simulation results showed that compared with three related protocols, QTGrid has lower energy consumption and higher spatial query efficiency and is more suitable for large-scale WSN spatial query application scenarios.

Freeform optical design for a nonscanning corneal imaging system with a convexly curved image.

Most existing techniques that are typically used by specialists to image the cornea are based on point, slit, or annular scanning due to a narrow field of view. The difficulty in achieving a larger field of view comes from the convex shape of the human eyeball. Field curvature for a refractive imaging system with positive power is typically negative and thus a concave image surface. In order to view the full cornea and sclera with snapshot imaging, we calculate qualified two- and three-mirror solutions from Seidel aberration theory. A three-mirror solution is further optimized as a high-resolution off-axis imaging system using freeform surfaces, which can obtain a full-field tailored image shell without scanning. The lateral resolution on the cornea is about 10 µm with good modulation transfer function (MTF) and spot performance. To ease the assembly, a monolithic design is achieved with slightly lower resolution, leading to a potential mass production solution.

Multifield direct design method for ultrashort throw ratio projection optics with two tailored mirrors.

In this work, we present a multifield direct design method for ultrashort throw ratio projection optics. The multifield design method allows us to directly calculate two freeform mirror profiles, which are fitted by odd polynomials and imported into an optical design program as an excellent starting point. Afterward, these two mirrors are represented by XY polynomial freeform surfaces for further optimization. The final configuration consists of an off-the-shelf projection lens and two XY polynomial freeform mirrors to greatly shorten the regular projection distance from 2 m to 48 cm for a 78.3 inch diagonal screen. The values of the modulation transfer function for the optimized freeform mirror system are improved to over 0.6 at 0.5 lp/mm, in comparison with its rotationally symmetric counterpart's 0.43, and the final distortion is less than 1.5%, showing a very good and well-tailored imaging performance over the entire field of view.

Multi-fields direct design approach in 3D: calculating a two-surface freeform lens with an entrance pupil for line imaging systems.

Including an entrance pupil in optical systems provides clear benefits for balancing the overall performance of freeform and/or rotationally symmetric imaging systems. Current existing direct design methods that are based on perfect imaging of few discrete ray bundles are not well suited for wide field of view systems. In this paper, a three-dimensional multi-fields direct design approach is proposed to balance the full field imaging performance of a two-surface freeform lens. The optical path lengths and image points of numerous fields are calculated during the procedures, wherefore very few initial parameters are needed in advance. Design examples of a barcode scanner lens as well as a line imaging objective are introduced to demonstrate the effectiveness of this method.

[Study of Spectral Property and Measurement of Linear Variable Filters].

Linear variable filters (LVF) are widely used in a variety of small rapid spectrometric detecting devices. In the present paper, the splitting property of LVF was studied, and the spectral-property expression in Gaussian form was given, and the relationship between indexes of expression and LVF center transmission, width of spectrum, and linear dispersion was specified. Measurement based on monochromator for imaging spectrometers calibration was introduced, the sensitivity for detection system was discussed, and the tolerance was analyzed. It was shown that the slit displacement of monochromator relative to the optical axle and the slope of LVF affect the detecting accuracy most, and the tolerance can be reduced by adjustment of optical path and structure to reach requirement. System was built and the detection for spectral property of sample LVF was made. The result of data processing indicates that MSE for center transmission detection was lower than 0.05%, and the accuracy of this method was proved. Reference-parameters of relevant system designing and calibrating based on the LVF can be provided by this method.

[Manufacture tolerance analysis of solid Mach-Zehnder interferometer in large aperture static imaging spectrometer (LASIS)].

The principle and instrumental structure of large aperture static imaging spectrometer (LASIS) were briefly described in the present paper, the principle of the Mach-Zehnder imaging spectrometer was introduced, and the Mach-Zehnder interferometers' working way in the imaging spectrometer was illustrated. The structure of solid Mach-Zehnder interferometer was analyzed, and discussion was made based on the requirements of field of view (FOV) in image space and single sided interferogram with a small portion around zero path difference (ZPD). The additional optical path difference (OPD) created by manufacturing and matching tolerance of two asymmetrical pentagonal prisms will lead to the displacement of shearing and OPD nonlinearity. It was showed that the additional OPD from non-common optical path structure of solid Mach-Zehnder spectrometer implies more requirements on the manufacture of this element, compared with Sagnac interferometer, for the matching tolerance of two asymmetrical pentagonal prisms to br lower than 0.02 mm. The recovery spectrum error caused by the OPD nonlinearity is lower than 0.2% and can be ignored.

Correcting Optical Aberration via Depth-Aware Point Spread Functions.

Optical aberration is a ubiquitous degeneration in realistic lens-based imaging systems. Optical aberrations are caused by the differences in the optical path length when light travels through different regions of the camera lens with different incident angles. The blur and chromatic aberrations manifest significant discrepancies when the optical system changes. This work designs a transferable and effective image simulation system of simple lenses via multi-wavelength, depth-aware, spatially-variant four-dimensional point spread functions (4D-PSFs) estimation by changing a small amount of lens-dependent parameters. The image simulation system can alleviate the overhead of dataset collecting and exploiting the principle of computational imaging for effective optical aberration correction. With the guidance of domain knowledge about the image formation model provided by the 4D-PSFs, we establish a multi-scale optical aberration correction network for degraded image reconstruction, which consists of a scene depth estimation branch and an image restoration branch. Specifically, we propose to predict adaptive filters with the depth-aware PSFs and carry out dynamic convolutions, which facilitate the model's generalization in various scenes. We also employ convolution and self-attention mechanisms for global and local feature extraction and realize a spatially-variant restoration. The multi-scale feature extraction complements the features across different scales and provides fine details and contextual features. Extensive experiments demonstrate that our proposed algorithm performs favorably against state-of-the-art restoration methods.

Occupational Exposure to Silica Dust and Silicosis Risk in Chinese Noncoal Mines: Qualitative and Quantitative Risk Assessment.

BACKGROUND: Despite increasing awareness, silica dust-induced silicosis still contributes to the huge disease burden in China. Worryingly, recent silica dust exposure levels and silicosis risk in Chinese noncoal mines remain unclear. OBJECTIVE: We aimed to determine recent silica dust exposure levels and assess the risk of silicosis in Chinese noncoal mines. METHODS: Between May and December 2020, we conducted a retrospective cohort study on 3 noncoal mines and 1 public hospital to establish, using multivariable Cox regression analyses, prediction formulas of the silicosis cumulative hazard ratio (H) and incidence (I) and a cross-sectional study on 155 noncoal mines in 10 Chinese provinces to determine the prevalence of silica dust exposure (PDE), free silica content, and total dust and respirable dust concentrations. The qualitative risk of silicosis was assessed using the International Mining and Metals Commission's risk-rating table and the occupational hazard risk index; the quantitative risk was assessed using prediction formulas. RESULTS: Kaplan-Meier survival analysis revealed significant differences in the silicosis probability between silica dust-exposed male and female miners (log-rank test χ21=7.52, P=.01). A total of 126 noncoal mines, with 29,835 miners and 4623 dust samples, were included; 13,037 (43.7%) miners were exposed to silica dust, of which 12,952 (99.3%) were male. The median PDE, free silica content, total dust concentration, and respirable dust concentration were 61.6%, 27.6%, 1.30 mg/m3, and 0.58 mg/m3, respectively, indicating that miners in nonmetal, nonferrous metal, small, and open-pit mines suffer high-level exposure to silica dust. Comprehensive qualitative risk assessment showed noncoal miners had a medium risk of silicosis, and the risks caused by total silica dust and respirable silica dust exposure were high and medium, respectively. When predicting H and I over the next 10, 20, and 30 years, we assumed that the miner gender was male. Under exposure to current total silica dust concentrations, median I10, I20, and I30 would be 6.8%, 25.1%, and 49.9%, respectively. Under exposure to current respirable silica dust concentrations, median I10, I20, and I30 would be 6.8%, 27.7%, and 57.4%, respectively. These findings showed that miners in nonmetal, nonferrous metal, small, and open-pit mines have a higher I and higher qualitative silicosis risk. CONCLUSIONS: Chinese noncoal miners, especially those in nonmetal, nonferrous metal, small, and open-pit mines, still suffer high-level exposure to silica dust and a medium-level risk of silicosis. Data of both total silica dust and respirable silica dust are vital for occupational health risk assessment in order to devise effective control measures to reduce noncoal mine silica dust levels, improve miners' working environment, and reduce the risk of silicosis.

Fabrication of large-scale scaffolds with microscale features using light sheet stereolithography.

The common characteristics that make scaffolds suitable for human tissue substitutes include high porosity, microscale features, and pores interconnectivity. Too often, however, these characteristics are limiting factors for the scalability of different fabrication approaches, particularly in bioprinting techniques, in which either poor resolution, small areas, or slow processes hinder practical use in certain applications. An excellent example is bioengineered scaffolds for wound dressings, in which microscale pores in large surface-to-volume ratio scaffolds must be manufactured - ideally fast, precise, and cheap, and where conventional printing methods do not readily meet both ends. In this work, we propose an alternative vat photopolymerization technique to fabricate centimeter-scale scaffolds without losing resolution. We used laser beam shaping to first modify the profile of the voxels in 3D printing, resulting in a technology we refer to as light sheet stereolithography (LS-SLA). For proof of concept, we developed a system from commercially available off-the-shelf components to demonstrate strut thicknesses up to 12.8 ± 1.8 µm, tunable pore sizes ranging from 36 µm to 150 µm, and scaffold areas up to 21.4 mm × 20.6 mm printed in a short time. Furthermore, the potential to fabricate more complex and three-dimensional scaffolds was demonstrated with a structure composed of six layers, each rotated by 45° with respect to the previous. Besides the demonstrated high resolution and achievable large scaffold sizes, we found that LS-SLA has great potential for scaling-up of applied oriented technology for tissue engineering applications.

Multi-scale, multi-dimensional binocular endoscopic image depth estimation network.

During invasive surgery, the use of deep learning techniques to acquire depth information from lesion sites in real-time is hindered by the lack of endoscopic environmental datasets. This work aims to develop a high-accuracy three-dimensional (3D) simulation model for generating image datasets and acquiring depth information in real-time. Here, we proposed an end-to-end multi-scale supervisory depth estimation network (MMDENet) model for the depth estimation of pairs of binocular images. The proposed MMDENet highlights a multi-scale feature extraction module incorporating contextual information to enhance the correspondence precision of poorly exposed regions. A multi-dimensional information-guidance refinement module is also proposed to refine the initial coarse disparity map. Statistical experimentation demonstrated a 3.14% reduction in endpoint error compared to state-of-the-art methods. With a processing time of approximately 30fps, satisfying the requirements of real-time operation applications. In order to validate the performance of the trained MMDENet in actual endoscopic images, we conduct both qualitative and quantitative analysis with 93.38% high precision, which holds great promise for applications in surgical navigation.

TXNL4B regulates radioresistance by controlling the PRP3-mediated alternative splicing of FANCI.

Ionizing radiation (IR) has been extensively used for cancer therapy, but the radioresistance hinders and undermines the radiotherapy efficacy in clinics greatly. Here, we reported that the spliceosomal protein thioredoxin-like 4B (TXNL4B) is highly expressed in lung tissues from lung cancer patients with radiotherapy. Lung cancer cells with TXNL4B knockdown illustrate increased sensitivity to IR. Mechanistically, TXNL4B interacts with RNA processing factor 3 (PRP3) and co-localizes in the nucleus post-IR. Nuclear localization of PRP3 promotes the alternative splicing of the Fanconi anemia group I protein (FANCI) transcript variants, FANCI-12 and FANCI-13. PRP3 regulates alternative splicing of FANCI toward the two variants, FANCI-12 and FANCI-13. Radioresistance was greatly enhanced through the combination of PRP31 and PRP8, the critical components of core spliceosome promoted by PRP3. Notably, the inhibition of PRP3 to suppress the production of FANCI-12 would deprive PRP31 and PRP8 of such interaction. As a result, cell cycle G2/M arrest was induced, DNA damage repair was delayed, and radiosensitivity was improved. Collectively, our study highlights potential novel underlying mechanisms of the involvement of TXNL4B and alternative splicing in radioresistance. The results would benefit potential cancer radiotherapy.

Miniaturized, high numerical aperture confocal fluorescence detection enhanced with pyroelectric droplet accumulation for sub-attomole analyte diagnosis.

To meet the growing demand for early fatal disease screening among large populations, current fluorescence detection instruments aiming at point-of-care diagnosis have the tendency to be low cost and high sensitivity, with a high potential for the analysis of low-volume, multiplex analytes with easy operation. In this work, we present the development of a miniaturized, high numerical aperture confocal fluorescence scanner for sub-micro-liter fluid diagnosis. It is enhanced with high-rate analyte accumulation using a pyroelectro-hydrodynamic dispensing system for generating tiny, stable sample droplets. The simplified confocal fluorescence scanner (numerical aperture 0.79, working distance 7.3 mm) uses merely off-the-shelf mass-production optical components. Experimental results show that it can achieve a high-sensitive, cost-efficient detection for sub-micro-liter, low-abundant (0.04 µL, 0.67 attomoles) fluid diagnosis, promising for point-of-care diagnosis.