Visualizing Quaternion Multiplication

Quaternion rotation is a powerful tool for rotating vectors in 3-D; as a result, it has been used in various engineering fields, such as navigations, robotics, and computer graphics. However, understanding it geometrically remains challenging, because it requires visualizing 4-D spaces, which makes exploiting its physical meaning intractable. In this paper, we provide a new geometric interpretation of quaternion multiplication using a movable 3-D space model, which is useful for describing quaternion algebra in a visual way. By interpreting the axis for the scalar part of quaternion as a 1-D translation axis of 3-D vector space, we visualize quaternion multiplication and describe it as a combined effect of translation, scaling, and rotation of a 3-D vector space. We then present how quaternion rotation formulas and the derivative of quaternions can be formulated and described under the proposed approach.112sciescopu

Sparse Variational Deterministic Policy Gradient for Continuous Real Time Control

Recent advancements in deep reinforcement learning for real control tasks have received interest from many researchers and field engineers in a variety of industrial areas. However, in most cases, optimal policies obtained by deep reinforcement learning are difficult to implement on cost-effective and lightweight platforms such as mobile devices. This can be attributed to their computational complexity and excessive memory usage. For this reason, this study proposes an off-policy deep reinforcement learning algorithm called the sparse variational deterministic policy gradient (SVDPG). SVDPG provides highly efficient policy network compression under the standard reinforcement learning framework. The proposed SVDPG integrates Bayesian pruning, which is known as a state-of-the-art neural network compression technique, with the policy update in an actor-critic architecture for reinforcement learning. It is demonstrated that SVDPG achieves a high compression rate of policy networks for continuous control benchmark tasks while preserving a competitive performance. The superiority of SVDPG in low-computing power devices is proven by comparing the level of compression in terms of the memory requirements and computation time on a commercial microcontroller unit. Finally, it is confirmed that the proposed SVDPG is also reliable in real-world scenarios since it can be applied to the swing-up control of an inverted pendulum system.11Nsciescopu

Interference-Compensating Magnetometer Calibration With Estimated Measurement Noise Covariance for Application to Small-Sized UAVs

This article proposes a new interference-compensating magnetometer calibration scheme aided by a gyroscope sensor, which could reduce the effect of induced magnetic interference due to nearby onboard current flow. By using the innovation process and a linear matrix inequality approach, mean and variance of the induced magnetic interference are estimated to ensure that their physical meaningful values are taken to be closest to the empirically measured ones. The values are reflected in the update step of the extended Kalman filter in order to accurately estimate the calibration parameters and the corresponding direction. Results of experiments performed using a real unmanned aerial vehicle (UAV) demonstrate that the proposed calibration scheme compensates well for the disturbing magnetic interference arising from the UAV's onboard current and hence reduces the estimation error of its yaw angle, or its heading direction, by approximately two-thirds of that obtained using the existing scheme.11Nsciescopu

Phytochemical and functional characterization of fermented Yerba mate using Rhizopus oligosporus

Abstract Solid-state fermentation (SSF) was used to enhance the bioactive compounds and biological properties of food materials, such as buckwheat, turmeric, and ginseng. This study was investigated the effects of SSF for up to 10 days using Rhizopus oligosporus on Yerba mate (Ilex paraguariensis St. Hilaire). The total phenolic content of Yerba mate rose to 20% after 1 day fermentation. The saponin contents of Yerba mate rose to 38% after 7 day fermentation. Furthermore, chlorogenic acid, caffeic acid, and caffeine levels were increased up to 27.74% by fermentation, as determined by UPLC-MS analysis. ORAC and FRAP assays showed that the antioxidant activities of Yerba mate were enhanced 1.9- and 1.14-fold after 1 day fermentation. In addition, its inhibitory activities against yeast α-glucosidase and nitric oxide release in LPS-stimulated RAW264.7 cells were higher than in the unfermented Yerba mate. Moreover, taste sensory analysis using an electronic tongue sensory system showed that the flavor of Yerba mate after 1 day fermentation was similar to that of the unfermented Yerba mate. These results suggested that solid fermentation using R. oligosporus is conducive to producing Yerba mate with enhanced biological properties

Anti-Aging and Lightening Effects of Au-Decorated Zeolite-Based Biocompatible Nanocomposites in Epidermal Delivery Systems

The main challenges in developing zeolites as cosmetic drug delivery systems are their cytotoxicities and the formation of drug-loading pore structures. In this study, Au-decorated zeolite nanocomposites were synthesized as an epidermal delivery system. Thus, 50 nm-sized Au nanoparticles were successfully deposited on zeolite 13X (super cage (α) and sodalite (β) cage structures) using the Turkevich method. Various cosmetic drugs, such as niacinamide, sulforaphane, and adenosine, were loaded under in vitro and in vivo observations. The Au-decorated zeolite nanocomposites exhibited effective cosmetic drug-loading efficiencies of 3.5 to 22.5 wt% under various conditions. For in vitro cytotoxic observations, B16F10 cells were treated with various cosmetic drugs. Niacinamide, sulforaphane, and adenosine-loaded Au-decorated zeolite nanocomposites exhibited clear cell viability of over 80%. Wrinkle improvement and a reduction in melanin content on the skin surface were observed in vivo. The adenosine delivery system exhibited an enhanced wrinkle improvement of 203% compared to 0.04 wt% of the pure adenosine system. The niacinamide- and sulforaphane-loaded Au-decorated zeolite nanocomposites decreased the skin surface melanin content by 123% and 222%, respectively, compared to 2 and 0.01 wt% of pure niacinamide and sulforaphane systems, respectively. As a result, Au-decorated zeolite nanocomposites show great potential as cosmetic drug epidermal delivery systems for both anti-aging and lightening effects

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning

Abstract Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation. The deep learning model, which was trained using over 11 million images, showed good performance with a global accuracy of 98.92%, a weighted intersection over the union of 0.9841, and a mean boundary F1 score of 0.8921. Moreover, deep learning performed 5–8 times faster than the experts’ recognition performed manually, which is comparatively inefficient, with almost the same significance. This study will play an important role in preoperative surgical planning for trauma surgery with convenience and speed