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Background Titanium dioxide (TiO 2 ) nanoparticles are among the most manufactured nanomaterials in the industry, and are used in food products, toothpastes, cosmetics and paints. Pregnant women as well as their conceptuses may be exposed to TiO 2 nanoparticles; however, the potential effects of these nanoparticles during pregnancy are controversial, and their internal distribution has not been investigated. Therefore, in this study, we investigated the potential effects of oral exposure to TiO 2 nanoparticles and their distribution during pregnancy. TiO 2 nanoparticles were orally administered to pregnant Sprague-Dawley rats (12 females per group) from gestation days (GDs) 6 to 19 at dosage levels of 0, 100, 300 and 1000 mg/kg/day, and then cesarean sections were conducted on GD 20. Results In the maternal and embryo-fetal examinations, there were no marked toxicities in terms of general clinical signs, body weight, food consumption, organ weights, macroscopic findings, cesarean section parameters and fetal morphological examinations. In the distribution analysis, titanium contents were increased in the maternal liver, maternal brain and placenta after exposure to high doses of TiO 2 nanoparticles. Conclusion Oral exposure to TiO 2 during pregnancy increased the titanium concentrations in the maternal liver, maternal brain and placenta, but these levels did not induce marked toxicities in maternal animals or affect embryo-fetal development. These results could be used to evaluate the human risk assessment of TiO 2 nanoparticle oral exposure during pregnancy, and additional comprehensive toxicity studies are deemed necessary considering the possibility of complex exposure scenarios and the various sizes of TiO 2 nanoparticles.

In this paper, we present a novel integral imaging pickup method. We extract each pixel's actual depth data from a real object's surface using a depth camera, then generate elemental images based on the depth map. Since the proposed method generates elemental images without a lens array, it has simplified the pickup process and overcome some disadvantages caused by a conventional optical pickup process using a lens array. As a result, we can display a three-dimensional (3D) image in integral imaging. To show the usefulness of the proposed method, an experiment is presented. Though the pickup process has been simplified in the proposed method, the experimental results reveal that it can also display a full motion parallax image the same as the image reconstructed by the conventional method. In addition, if we improve calculation speed, it will be useful in a real-time integral imaging display system.

Cloud computing has attracted a great deal of attention in the education sector as a way of delivering more economical, securable, and reliable education services. This paper proposes and introduces a cloud-based smart education system for e-learning content services with a view to delivering and sharing various enhanced forms of educational content, including text, pictures, images, videos, 3-dimensional (3D) objects, and scenes of virtual reality (VR) and augmented reality (AR). The proposed system consists of six main features that are required for deploying cloud-based educational content services: 1) a cloud platform that provides an infrastructure for the realization of a cloud-based educational media service environment, 2) a compatible file format that enables it to provide media content through various types of devices, 3) an authoring tool that enables teachers to create various types of media content, 4) a content viewer that displays different types of media on multiple platforms, 5) an infer-ence engine that provides students with individualized learning content, and 6) a security system that manages privileged user access and data encryption in the cloud for dependable educational content services. We believe that the proposed system should provide a new and innovative solution for cloud-based educational media services by supporting a cloud-based service environment with a totally integrated system.

In an integral imaging display, the computer-generated integral imaging method has been widely used to create the elemental images from a given three-dimensional object data. Long processing time, however, has been problematic especially when the three-dimensional object data set or the number of the elemental lenses are large. In this paper, we propose an image space parallel processing method, which is implemented by using Open Computer Language (OpenCL) for rapid generation of the elemental images sets from large three-dimensional volume data. Using the proposed technique, it is possible to realize a real-time interactive integral imaging display system for 3D volume data constructed from computational tomography (CT) or magnetic resonance imaging (MRI) data.

A real-time interactive orthographic-view image display of integral imaging (II) microscopy that includes the generation of intermediate-view elemental images (IVEIs) for resolution enhancement is proposed. Unlike the conventional II microscopes, parallel processing through a graphics processing unit is required for real-time display that generates the IVEIs and interactive orthographic-view images in high speed, according to the user interactive input. The real-time directional-view display for the specimen for which 3D information is acquired through II microscopy is successfully demonstrated by using resolution-enhanced elemental image arrays. A user interactive feature is also satisfied in the proposed real-time interactive display for II microscopy.

Due to the limitations of micro lens arrays and camera sensors, images on display devices through the integral imaging microscope systems have been suffering for a low-resolution. In this paper, a resolution-enhanced orthographic-view image display method for integral imaging microscopy is proposed and demonstrated. Iterative intermediate-view reconstructions are performed based on bilinear interpolation using neighborhood elemental image information, and a graphics processing unit parallel processing algorithm is applied for fast image processing. The proposed method is verified experimentally and the effective results are presented in this paper.

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