TECHNICAL ANALYSIS OF AIR RIFLE SHOOTING IN ELITE SHOOTERS

INTRODUCTION: The Chinese National Shooting Team has consistently won gold medals in the Olympic Games since 1984 (with the exception of 1988). This raises the question of why the Chinese National Shooting Team has produced so many champions and what principles were applied in the shooting performance. The purpose of this study was to provide research on principles of the shooting performance by testing Chinese elite shooters using the Noptel ST-2000 made in Finland, and to establish a technical analysis model of shooting performance. Successful shooting performance is considered to be the product of three basic technical factors: hold, aim and trigger control. A shooter’s hold is demonstrated by his ability to control specific muscles and to prevent unwanted movement. Aim is related to the accuracy with which the subject is able to direct the gun at the desired point on the target. Finally, trigger control is denoted by the timing of the actual triggering event, relative to the hold/aim process and the cleanness with which triggering took place

AI-Based Collaborative Teaching: Strategies and Analysis in Visual Communication Design

With the rapid development of technology, AI has been widely applied in multiple fields, especially the field of education. As a discipline involving art, technology and creativity, visual communication design is facing the challenge of keeping up with the times and combining new technologies for innovation. Collaborative teaching model emphasizes multi-party participation and collaborative learning, and its proposal has injected new vitality into traditional educational patterns. However, existing studies, which combine collaborative teaching model with artificial intelligence, still have limitations in application and practice, and most of them remain in the theoretical discussion stage and lack empirical support. This study aimed to make up for this deficiency. After in-depth analysis of educational data, a forecasting model of collaborative teaching demand based on AI was proposed. Course content suitable for the collaborative teaching model was further planned for the education in visual communication design

Dataset Distillation: A Comprehensive Review

Recent success of deep learning is largely attributed to the sheer amount of data used for training deep neural networks.Despite the unprecedented success, the massive data, unfortunately, significantly increases the burden on storage and transmission and further gives rise to a cumbersome model training process. Besides, relying on the raw data for training \emph{per se} yields concerns about privacy and copyright. To alleviate these shortcomings, dataset distillation~(DD), also known as dataset condensation (DC), was introduced and has recently attracted much research attention in the community. Given an original dataset, DD aims to derive a much smaller dataset containing synthetic samples, based on which the trained models yield performance comparable with those trained on the original dataset. In this paper, we give a comprehensive review and summary of recent advances in DD and its application. We first introduce the task formally and propose an overall algorithmic framework followed by all existing DD methods. Next, we provide a systematic taxonomy of current methodologies in this area, and discuss their theoretical interconnections. We also present current challenges in DD through extensive experiments and envision possible directions for future works.Comment: 23 pages, 168 references, 8 figures, under revie

DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation

One key challenge of exemplar-guided image generation lies in establishing fine-grained correspondences between input and guided images. Prior approaches, despite the promising results, have relied on either estimating dense attention to compute per-point matching, which is limited to only coarse scales due to the quadratic memory cost, or fixing the number of correspondences to achieve linear complexity, which lacks flexibility. In this paper, we propose a dynamic sparse attention based Transformer model, termed Dynamic Sparse Transformer (DynaST), to achieve fine-level matching with favorable efficiency. The heart of our approach is a novel dynamic-attention unit, dedicated to covering the variation on the optimal number of tokens one position should focus on. Specifically, DynaST leverages the multi-layer nature of Transformer structure, and performs the dynamic attention scheme in a cascaded manner to refine matching results and synthesize visually-pleasing outputs. In addition, we introduce a unified training objective for DynaST, making it a versatile reference-based image translation framework for both supervised and unsupervised scenarios. Extensive experiments on three applications, pose-guided person image generation, edge-based face synthesis, and undistorted image style transfer, demonstrate that DynaST achieves superior performance in local details, outperforming the state of the art while reducing the computational cost significantly. Our code is available at https://github.com/Huage001/DynaSTComment: ECCV 202

Castration modulates singing patterns and electrophysiological properties of RA projection neurons in adult male zebra finches

Castration can change levels of plasma testosterone. Androgens such as testosterone play an important role in stabilizing birdsong. The robust nucleus of the arcopallium (RA) is an important premotor nucleus critical for singing. In this study, we investigated the effect of castration on singing patterns and electrophysiological properties of projection neurons (PNs) in the RA of adult male zebra finches. Adult male zebra finches were castrated and the changes in bird song assessed. We also recorded the electrophysiological changes from RA PNs using patch clamp recording. We found that the plasma levels of testosterone were significantly decreased, song syllable’s entropy was increased and the similarity of motif was decreased after castration. Spontaneous and evoked firing rates, membrane time constants, and membrane capacitance of RA PNs in the castration group were lower than those of the control and the sham groups. Afterhyperpolarization AHP time to peak of spontaneous action potential (AP) was prolonged after castration.These findings suggest that castration decreases song stereotypy and excitability of RA PNs in male zebra finches

Dopamine modulates synaptic transmission in the premotor nuclei of songbirds

Songbirds, such as zebra finches, contribute to explore behaviors underlying neural activities. Birdsong is controlled by the song system. The robust nucleus of the arcopallium (RA) is a key nucleus for producing birdsong in the song system. The RA receives dopaminergic （DArgic） inputs from the midbrain, however, the function of these inputs involved excitatory synaptic transmission is still unclear. Excitatory synaptic transmission is critical in the signal integration activities of the brain. We examined the effects of dopamine (DA) on excitatory synaptic transmission of the projection neurons in the RA of adult male zebra finches, using whole-cell recording technique. We found that DA (100 μM) decreases the frequency of spontaneous and miniature excitatory postsynaptic currents (sEPSCs/mEPSCs). In our further study, these effects of DA were reversed by the D1-like dopamine receptor (D1R) antagonist and stimulated by a D1R agonist. However, a D2-like dopamine receptor (D2R) has no influence on the effects of DA. These results demonstrate that DA can inhibit excitatory synaptic transmission mainly via activation of D1R in adult male zebra finches. PeerJ PrePrints | https://doi.org/10.7287/peerj.preprints.1563v1 | CC-BY 4.0 Open Access