Design for Tea

From a perspective of a young Chinese person, I noticed that lots of Chinese youth who like me neither drink tea daily nor understand the cultural meaning of tea. It is concerning that the lack of awareness of tea among Chinese youth might lead to the loss of Chinese tea culture. In this thesis project, I will introduce a system of portable teaware design focused on motivating users to enjoy the true beauty of tea, and so inspiring them to reassess their understanding of tea and themselves

Pre-IdentifyNet: An Improved Neural Network for Image Recognition

With the rise and development of artificial intelligence, image recognition and classification technology has received more and more attention as an important branch of its research field. Among them, the introduction of deep learning networks and the construction of neural network structures not only avoid a lot of the tedious work of manual extraction, but also improve the accuracy of image recognition. Convolutional neural networks have many advantages that conventional neural networks do not have. Therefore, image classification systems based on convolutional neural networks emerge in endlessly, but there is still much room for improvement in terms of recognition accuracy and recognition speed. Based on this, this paper proposes an improved deep convolutional neural network to improve the accuracy of the network by changing a series of parameters such as the number of channels of the convolution layer, the size of the convolution kernel, the learning rate, the number of iterations, and the size of the small batch with speed. In this paper, three data sets were selected, namely sewage, animals and the Simpson Family. Comparing the improved convolutional neural network network with the existing SqueezeNet and GoogleNet. It is found that the accuracy of the network is maintained while maintaining a similar speed. Both F1-score and F1-score have been improved with a higher recognition rate and better recognition effect in image recognition classification

Enhanced Fireworks Algorithm-Auto Disturbance Rejection Control Algorithm for Robot Fish Path Tracking

The robot fish is affected by many unknown internal and external interference factors when it performs path tracking in unknown waters. It was proposed that a path tracking method based on the EFWA-ADRC (enhanced fireworks algorithmauto disturbance rejection control) to obtain high-quality tracking effect. ADRC has strong adaptability and robustness. It is an effective method to solve the control problems of nonlinearity, uncertainty, strong interference, strong coupling and large time lag. For the optimization of parameters in ADRC, the enhanced fireworks algorithm (EFWA) is used for online adjustment. It is to improve the anti-interference of the robot fish in the path tracking process. The multi-joint bionic robot fish was taken as the research object in the paper. It was established a path tracking error model in the Serret-Frenet coordinate system combining the mathematical model of robotic fish. It was focused on the forward speed and steering speed control rate. It was constructed that the EFWA-ADRC based path tracking system. Finally, the simulation and experimental results show that the control method based on EFWAADRC and conventional ADRC makes the robotic fish track the given path at 2:8s and 3:3s respectively, and the tracking error is kept within plus or minus 0:09m and 0:1m respectively. The new control method tracking steady-state error was reduces by 10% compared with the conventional ADRC. It was proved that the proposed EFWA-ADRC controller has better control effect on the controlled system, which is subject to strong interference

Distributed bundle adjustment with block-based sparse matrix compression for super large scale datasets

We propose a distributed bundle adjustment (DBA) method using the exact Levenberg-Marquardt (LM) algorithm for super large-scale datasets. Most of the existing methods partition the global map to small ones and conduct bundle adjustment in the submaps. In order to fit the parallel framework, they use approximate solutions instead of the LM algorithm. However, those methods often give sub-optimal results. Different from them, we utilize the exact LM algorithm to conduct global bundle adjustment where the formation of the reduced camera system (RCS) is actually parallelized and executed in a distributed way. To store the large RCS, we compress it with a block-based sparse matrix compression format (BSMC), which fully exploits its block feature. The BSMC format also enables the distributed storage and updating of the global RCS. The proposed method is extensively evaluated and compared with the state-of-the-art pipelines using both synthetic and real datasets. Preliminary results demonstrate the efficient memory usage and vast scalability of the proposed method compared with the baselines. For the first time, we conducted parallel bundle adjustment using LM algorithm on a real datasets with 1.18 million images and a synthetic dataset with 10 million images (about 500 times that of the state-of-the-art LM-based BA) on a distributed computing system.Comment: camera ready version for ICCV202

Disruption of Smad7 Promotes ANG II-Mediated Renal Inflammation and Fibrosis via Sp1-TGF-β/Smad3-NF.κB-Dependent Mechanisms in Mice

Smad7 is an inhibitory Smad and plays a protective role in obstructive and diabetic kidney disease. However, the role and mechanisms of Smad7 in hypertensive nephropathy remains unexplored. Thus, the aim of this study was to investigate the role and regulatory mechanisms of Smad7 in ANG II-induced hypertensive nephropathy. Smad7 gene knockout (KO) and wild-type (WT) mice received a subcutaneous infusion of ANG II or control saline for 4 weeks via osmotic mini-pumps. ANG II infusion produced equivalent hypertension in Smad7 KO and WT mice; however, Smad7 KO mice exhibited more severe renal functional injury as shown by increased proteinuria and reduced renal function (both p<0.05) when compared with Smad7 WT mice. Enhanced renal injury in Smad7 KO mice was associated with more progressive renal fibrosis with elevated TGF-β/Smad3 signalling. Smad7 KO mice also showed more profound renal inflammation including increased macrophage infiltration, enhanced IL-1β and TNF-α expression, and a marked activation of NF-κB signaling (all p<0.01). Further studies revealed that enhanced ANG II-mediated renal inflammation and fibrosis in Smad7 KO mice were also associated with up-regulation of Sp1 but downregulation of miR-29b expression. Taken together, the present study revealed that enhanced Sp1-TGF-β1/Smad3-NF-κB signaling and loss of miR-29 may be mechanisms by which deletion of Smad7 promotes ANG II-mediated renal fibrosis and inflammation. Thus, Smad7 may play a protective role in ANG II-induced hypertensive kidney disease. © 2013 Liu et al.published_or_final_versio

Decreased RNA polymerase III subunit expression leads to defects in oligodendrocyte development

IntroductionRNA polymerase III (Pol III) is a critical enzymatic complex tasked with the transcription of ubiquitous non-coding RNAs including 5S rRNA and all tRNA genes. Despite the constitutive nature of this enzyme, hypomorphic biallelic pathogenic variants in genes encoding subunits of Pol III lead to tissue-specific features and cause a hypomyelinating leukodystrophy, characterized by a severe and permanent deficit in myelin. The pathophysiological mechanisms in POLR3- related leukodystrophy and specifically, how reduced Pol III function impacts oligodendrocyte development to account for the devastating hypomyelination seen in the disease, remain poorly understood.MethodsIn this study, we characterize how reducing endogenous transcript levels of leukodystrophy-associated Pol III subunits affects oligodendrocyte maturation at the level of their migration, proliferation, differentiation, and myelination.ResultsOur results show that decreasing Pol III expression altered the proliferation rate of oligodendrocyte precursor cells but had no impact on migration. Additionally, reducing Pol III activity impaired the differentiation of these precursor cells into mature oligodendrocytes, evident at both the level of OL-lineage marker expression and on morphological assessment, with Pol III knockdown cells displaying a drastically more immature branching complexity. Myelination was hindered in the Pol III knockdown cells, as determined in both organotypic shiverer slice cultures and co-cultures with nanofibers. Analysis of Pol III transcriptional activity revealed a decrease in the expression of distinct tRNAs, which was significant in the siPolr3a condition.DiscussionIn turn, our findings provide insight into the role of Pol III in oligodendrocyte development and shed light on the pathophysiological mechanisms of hypomyelination in POLR3-related leukodystrophy

A New Hybrid Method in Global Dynamic Path Planning of Mobile Robot

Path planning and real-time obstacle avoidance is the key technologies of mobile robot intelligence. But the efficiency of the global path planning is not very high. It is not easy to avoid obstacles in real time. Aiming at these shortcomings it is proposed that a global dynamic path planning method based on improved A* algorithm and dynamic window method. At first the improved A* algorithm is put forward based on the traditional A* algorithm in the paper. Its optimized heuristic search function is designed. They can be eliminated that the redundant path points and unnecessary turning points. Simulation experiment 1 results show that the planned path length is reduced greatly. And the path transition points are less, too. And then it is focused on the global dynamic path planning of fusion improved A* Algorithm and Dynamic Window Method. The evaluation function is constructed taking into account the global optimal path. The real time dynamic path is planning. On the basis of ensuring the optimal global optimization of the planning path, it is improved that the smoothness of the planning path and the local real-time obstacle avoidance ability. The simulation experiments results show that the fusion algorithm is not only the shorter length, but also the smoother path compared the traditional path planning algorithms with the fusion algorithm in the paper. It is more fit to the dynamics of the robot control. And when a dynamic obstacle is added, the new path can be gained. The barrier can be bypass and the robot is to reach the target point. It can be guaranteed the global optimality of the path. Finally the Turtlebot mobile robot was used to experiment. The experimental results show that the global optimality of the proposed path can be guaranteed by the fusion algorithm. And the planned global path is smoother. When the random dynamic obstacle occurs in the experiment, the robot can be real-time dynamic obstacle avoidance. It can re-plan the path. It can bypass the random obstacle to reach the original target point. The outputting control parameters are more conducive to the robot’s automatic control. The fusion method is used for global dynamic path planning of mobile robots in this paper. In summary the experimental results show that the method is good efficiency and real-time performance. It has great reference value for the dynamic path planning application of mobile robot