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The near-eye display (NED) systems, designed to project content into the human eye, are pivotal in the realms of augmented reality (AR) and virtual reality (VR), offering users immersive experiences. A small volume is the key for a fashionable, easy-to-wear, comfortable NED system for industrial and consumer use. Freeform surfaces can significantly reduce the system volume and weight while improving the system specifications. However, great challenges still exist in further reducing the volume of near-eye display systems as there is also a limit when using only freeform optics. This paper introduces a novel method for designing compact freeform NED systems through a powerful optical-digital joint design. The method integrates a geometrical freeform optical design with deep learning of an image compensation neural network, addressing off-axis nonsymmetric structures with complex freeform surfaces. A design example is presented to demonstrate the effectiveness of the proposed method. Specifically, the volume of a freeform NED system is reduced by approximately 63% compared to the system designed by the traditional method, while still maintaining high-quality display performance. The proposed method opens a new pathway for the design of a next-generation ultra-compact NED system. [ABSTRACT FROM AUTHOR]

Studying the association between microbes and diseases not only aids in the prevention and diagnosis of diseases, but also provides crucial theoretical support for new drug development and personalized treatment. Due to the time‐consuming and costly nature of laboratory‐based biological tests to confirm the relationship between microbes and diseases, there is an urgent need for innovative computational frameworks to anticipate new associations between microbes and diseases. Here, we propose a novel computational approach based on a dual branch graph convolutional network (GCN) module, abbreviated as DBGCNMDA, for identifying microbe–disease associations. First, DBGCNMDA calculates the similarity matrix of diseases and microbes by integrating functional similarity and Gaussian association spectrum kernel (GAPK) similarity. Then, semantic information from different biological networks is extracted by two GCN modules from different perspectives. Finally, the scores of microbe–disease associations are predicted based on the extracted features. The main innovation of this method lies in the use of two types of information for microbe/disease similarity assessment. Additionally, we extend the disease nodes to address the issue of insufficient features due to low data dimensionality. We optimize the connectivity between the homogeneous entities using random walk with restart (RWR), and then use the optimized similarity matrix as the initial feature matrix. In terms of network understanding, we design a dual branch GCN module, namely GlobalGCN and LocalGCN, to fine‐tune node representations by introducing side information, including homologous neighbour nodes. We evaluate the accuracy of the DBGCNMDA model using five‐fold cross‐validation (5‐fold‐CV) technique. The results show that the area under the receiver operating characteristic curve (AUC) and area under the precision versus recall curve (AUPR) of the DBGCNMDA model in the 5‐fold‐CV are 0.9559 and 0.9630, respectively. The results from the case studies using published experimental data confirm a significant number of predicted associations, indicating that DBGCNMDA is an effective tool for predicting potential microbe–disease associations. [ABSTRACT FROM AUTHOR]

Coherence scanning interferometry (CSI) is a widely used non-contact method for measuring areal surface topography. The calculation of groove depth typically employs the 'W/3 rule' specified in ISO 5436-1. However, the batwing effect causes overshoots near the groove edges, which can introduce noise singularities in the selected W/3 region for depth calculation, thereby affecting the measurement of rectangular grating depth. This paper introduces the definition of batwing height and width and proposes a simulation model that considers various factors, such as the center wavelength, spectrum of the illuminating light, shadow effect, and numerical aperture, to analyze their influence on depth measurement. The simulation results demonstrate that the batwing width is the primary factor influencing depth measurement for small grating periods. Specifically, a decrease in numerical aperture increases the batwing width, leading to larger depth measurement errors, while a decrease in the center wavelength reduces the batwing width, resulting in smaller depth measurement errors. The influence of the illumination spectrum and shadow effect on depth measurement is found to be minor. Experimental validation using a step standard consisting of rectangular gratings with different periods and depths confirms the agreement between the experimental and simulated results. The proposed method provides a quantitative evaluation of depth measurement accuracy in CSI. [ABSTRACT FROM AUTHOR]

The Yushigou area in North Qilian, which is a research hotspot of thr paleo-oceanic basin, is located at the tectonic zone between the Alashane block and the Qaidam block at the north margin of the Qinghai-Tibet Plateau. The tectonic setting and the tectonic evolution of early Caledon at North Qilian is controversial, between rifted basin and oceanic basin. Some scholars believe that the north Qilian formed the matured ocean and the trench-arc-basin system in the early Ordovician period, while others insist that it just continued its rift valley evolution. In this study, the Axiosmax X-ray Fluorescence Spectrometer was used to measure the content of major elements and the X-Series 2 Inductively Coupled Plasma-Mass Spectrometry to measure the content of the trace elements and REE of the siliceous rocks collected from North Qilian. The results show that the mean ratio of Al/(Al+Fe+Mn) is 0.56 and 0.60, Al/(Al+Fe) is 0.57 and 0.61, (La/Yb)SN is 0.89 and 1.2, δCeSN is 0.88 and 0.93 and δEuSN is 1.15 and 1.08, for samples collected from two sites at Yushigou, respectively. Chondritic Standardized REEs distribution plot is a LREEs enrichment pattern which shows an outstanding rightward decreasing tendency. This evidence indicates that the tectonic settings of the siliceous rocks associated with subduction complex in Yushigou have a tectonic background of archipelagic ocean, of which some parts are close or far from the continental margin or the surrounding sea basin.