A focal stack camera, based on an electrically tunable-focusing liquid crystal (LC) lens doped with multi-walled carbon nanotubes, is proposed to generate a single all-in-focus image of a 3D scene without depth map in a relatively short time. Focal sweep strategy of the camera is devised. Both its depth of field (DOF) and focal sweep speed are analyzed and deduced. Nano doping method is adopted to improve electro-optical features of the LC lens. To efficiently produce all-in-focus image, a weighted average algorithm for all images in the focal stack is utilized. The experiments show that the result is a high contrast at sensor resolution. It is greatly potential in optical compact 3D imaging system.

Objectives To evaluate the efficacy and safety of single-dose intra-articular bupivacaine plus morphine after knee arthroscopic surgery. Design Meta-analysis. Data sources and study eligibility criteria A comprehensive literature search, using Medline (1966–2014), the Cochrane Central Register of Controlled Trials and Embase databases, was conducted to identify randomised placebo-controlled trials that used a combination of single-dose intra-articular bupivacaine and morphine for postoperative pain relief. Results 12 articles were included in this meta-analysis. The mean visual analogue scale (VAS) scores of the bupivacaine plus morphine group were significantly lower than those of the placebo group (weighted mean difference (WMD) −1.75; 95% CI −2.16 to −1.33; p<0.001). The VAS scores at the last follow-up time point (last VAS scores) of the bupivacaine plus morphine group were also significantly lower than those of the placebo group (WMD −1.46; 95% CI −1.63 to −1.29; p<0.001). The number of patients requiring supplementary analgesia was also significantly reduced (RR 0.60; 95% CI 0.39 to 0.93; p=0.02), while there was no significant difference in the time to first analgesic request (WMD 3.46; 95% CI −1.81 to 8.72; p=0.20) or short-term side effects (RR 1.67; 95% CI 0.65 to 4.26; p=0.29). Conclusions The administration of single-dose intra-articular bupivacaine plus morphine after knee arthroscopic surgery is effective for pain relief, and its short-term side effects remain similar to saline placebo.

In this paper, we present a novel design concept for determining the depth map of three-dimensional (3D) scenes based on an electrically controlled liquid crystal (LC) lens. The advantages of the proposed method are that it does not need any mechanical movements and a large amount of computations to acquire a depth map of a 3D scene in a relatively short amount of time. The tunable-focus LC lens doped with multi-walled carbon nanotubes is to become a key optical component for determining a depth map system. Sequenced two-dimensional images of slightly different perspectives are recorded in a short time, and the depth map of the 3D scene, according to a proposed depth estimation method and a focusing evaluation function, can be acquired in a simple way. This new method to acquire a depth map based on a doped LC lens maximizes the use of the proposed LC lens. The proposed system is novel in its compact, simple, and fast features, so we believe the proposed method can open a new creative dimension in image analysis and imaging systems and can also overcome the limitations of the conventional imaging mode.

This study demonstrates a light field display system using a nematic liquid crystal (LC) microlens array (MLA) and a polymer dispersed liquid crystal (PDLC) film. LC-MLA without polarization effects presented high-resolution intermediate 3D images by adopting a depolarization algorithm. The adopted PDLC film modulated the reconstructed 3D images to deliver full-parallax images efficiently with a wide FOV. The experimental result shows that the peak signal to noise ratio (PSNR) value of photograph accurate display results improves compared to the pure LC-MLA method. The proposed method is an essential step toward high-quality light field display.

Feature selection is a typical multiobjective problem including two conflicting objectives. In classification, feature selection aims to improve or maintain classification accuracy while reducing the number of selected features. In practical applications, feature selection is one of the most important tasks in remote sensing image classification. In recent years, many metaheuristic algorithms have attempted to explore feature selection, such as the dragonfly algorithm (DA). Dragonfly algorithms have a powerful search capability that achieves good results, but there are still some shortcomings, specifically that the algorithm’s ability to explore will be weakened in the late phase, the diversity of the populations is not sufficient, and the convergence speed is slow. To overcome these shortcomings, we propose an improved dragonfly algorithm combined with a directed differential operator, called BDA-DDO. First, to enhance the exploration capability of DA in the later stages, we present an adaptive step-updating mechanism where the dragonfly step size decreases with iteration. Second, to speed up the convergence of the DA algorithm, we designed a new differential operator. We constructed a directed differential operator that can provide a promising direction for the search, then sped up the convergence. Third, we also designed an adaptive paradigm to update the directed differential operator to improve the diversity of the populations. The proposed method was tested on 14 mainstream public UCI datasets. The experimental results were compared with seven representative feature selection methods, including the DA variant algorithms, and the results show that the proposed algorithm outperformed the other representative and state-of-the-art DA variant algorithms in terms of both convergence speed and solution quality.