Experimental Investigation of Relative Localization Estimation in a Coordinated Formation Control of Low-Cost Underwater Drones.

This study presents a relative localization estimation method for a group of low-cost underwater drones (l-UD), which only uses visual feedback provided by an on-board camera and IMU data. It aims to design a distributed controller for a group of robots to reach a specific shape. This controller is based on a leader-follower architecture. The main contribution is to determine the relative position between the l-UD without using digital communication and sonar positioning methods. In addition, the proposed implementation of the EKF to fuse the vision data and the IMU data improves the prediction capability in cases where the robot is out of view of the camera. This approach allows the study and testing of distributed control algorithms for low-cost underwater drones. Finally, three robot operating system (ROS) platform-based BlueROVs are used in an experiment in a near-realistic environment. The experimental validation of the approach has been obtained by investigating different scenarios.

eGAC3D: enhancing depth adaptive convolution and depth estimation for monocular 3D object pose detection.

Many alternative approaches for 3D object detection using a singular camera have been studied instead of leveraging high-precision 3D LiDAR sensors incurring a prohibitive cost. Recently, we proposed a novel approach for 3D object detection by employing a ground plane model that utilizes geometric constraints named GAC3D to improve the results of the deep-based detector. GAC3D adopts an adaptive depth convolution to replace the traditional 2D convolution to deal with the divergent context of the image's feature, leading to a significant improvement in both training convergence and testing accuracy on the KITTI 3D object detection benchmark. This article presents an alternative architecture named eGAC3D that adopts a revised depth adaptive convolution with variant guidance to improve detection accuracy. Additionally, eGAC3D utilizes the pixel adaptive convolution to leverage the depth map to guide our model for detection heads instead of using an external depth estimator like other methods leading to a significant reduction of time inference. The experimental results on the KITTI benchmark show that our eGAC3D outperforms not only our previous GAC3D but also many existing monocular methods in terms of accuracy and inference time. Moreover, we deployed and optimized the proposed eGAC3D framework on an embedded platform with a low-cost GPU. To the best of the authors' knowledge, we are the first to develop a monocular 3D detection framework on embedded devices. The experimental results on Jetson Xavier NX demonstrate that our proposed method can achieve nearly real-time performance with appropriate accuracy even with the modest hardware resource.

Design and synthesis of new lupeol derivatives and their α-glucosidase inhibitory and cytotoxic activities.

A series of lupeol derivatives 2, 2a-2f, 2a-2h, 3a-3e, and 4a-4b were designed, synthesised and evaluated for their α-glucosidase inhibitory and cytotoxic activities. Among synthetic derivatives, lupeol analogues 2b and 2e containing a benzylidene chain exhibited the best activity against α-glucosidase and superior to the positive agent with the IC50 values of 29.4 ± 1.33 and 20.1 ± 0.91 µM, respectively. Lupeol analogues 2d and 3a showed weak cytotoxicity against K562 cell line with the IC50 values of 76.6 ± 2.40 and 94.4 ± 1.51 µM, respectively.

GAC3D: improving monocular 3D object detection with ground-guide model and adaptive convolution.

Monocular 3D object detection has recently become prevalent in autonomous driving and navigation applications due to its cost-efficiency and easy-to-embed to existent vehicles. The most challenging task in monocular vision is to estimate a reliable object's location cause of the lack of depth information in RGB images. Many methods tackle this ill-posed problem by directly regressing the object's depth or take the depth map as a supplement input to enhance the model's results. However, the performance relies heavily on the estimated depth map quality, which is bias to the training data. In this work, we propose depth-adaptive convolution to replace the traditional 2D convolution to deal with the divergent context of the image's features. This lead to significant improvement in both training convergence and testing accuracy. Second, we propose a ground plane model that utilizes geometric constraints in the pose estimation process. With the new method, named GAC3D, we achieve better detection results. We demonstrate our approach on the KITTI 3D Object Detection benchmark, which outperforms existing monocular methods.

An adaptive weighting mechanism for Reynolds rules-based flocking control scheme.

Cooperative navigation for fleets of robots conventionally adopts algorithms based on Reynolds's flocking rules, which usually use a weighted sum of vectors for calculating the velocity from behavioral velocity vectors with corresponding fixed weights. Although optimal values of the weighting coefficients giving good performance can be found through many experiments for each particular scenario, the overall performance could not be guaranteed due to unexpected conditions not covered in experiments. This paper proposes a novel control scheme for a swarm of Unmanned Aerial Vehicles (UAVs) that also employs the original Reynolds rules but adopts an adaptive weight allocation mechanism based on the current context than being fixed at the beginning. The simulation results show that our proposed scheme has better performance than the conventional Reynolds-based ones in terms of the flock compactness and the reduction in the number of crashed swarm members due to collisions. The analytical results of behavioral rules' impact also validate the proposed weighting mechanism's effectiveness leading to improved performance.

Visible photodetector based on transition metal-doped ZnO NRs/PEDOT:PSS hybrid materials.

A hybrid Cu-doped ZnO nanorods (ZnO:Cu NRs)/poly(3,4 ethylene dioxythiophene)-polystyrene sulfonate (PEDOT:PSS)-based photodetector was fabricated using a simple hydrothermal method with pre-patterned silver electrodes. In the hybrid structure, PEDOT:PSS with high mobility acts as a carrier transport layer, while ZnO:Cu NRs with high visible absorption works as an "antenna" material to generate electron-hole pairs under light illumination. As a result, the devices exhibits a high response in visible light at a wavelength of 395 nm. The responsivity and photoconductive gain of the hybrid photodetector reached 0.33 A W-1 and 1.306, respectively, which is 1.36 times higher than those of Cu-doped ZnO NRs-based ones. The response and recovery times are improved, with values of 25.21 s and 42.01 s, respectively. The development of hybrid materials for visible photodetectors enables an innovative approach for future optoelectronic devices, especially optical sensors.

Tobacco and poverty: evidence from Vietnam.

This review examined existing evidence to investigate the link between tobacco and poverty in Vietnam, to assess the impact of tobacco control policies on employment related to tobacco consumption and to identify information gaps that require further research for the purposes of advocating stronger tobacco control policies. A Medline, PubMed and Google Scholar search identified studies addressing the tobacco and poverty association in Vietnam using extensive criteria. In all, 22 articles related either to tobacco and health or economics, or to the potential impact of tobacco control policies, were identified from titles, abstracts or the full text. 28 additional publications were identified by other means. PHA, LTT and LTTH reviewed the publications and prepared the initial literature review. There is extensive evidence that tobacco use contributes to poverty and inequality in Vietnam and that tobacco control policies would not have a negative impact on overall employment. Tobacco use wastes household and national financial resources and widens social inequality. The implementation and enforcement of a range of tobacco control measures could prove beneficial not only to improve public health but also to alleviate poverty.