BAR HEIGHTS NEEDED FOR SUCCESSFUL LIFTS IN MEN’S WEIGHTLIFTERS

The purpose of this study was to analyze the techniques of 132 Chinese male weightlifters competing at the 2015 China Weightlifting Championships, and to examine the differences of maximum bar height (MbH) and relative MbH (MbH/body height) among the all 8 weight classes. All attempts were recorded with the Real-Time Feedback System during the competition, and 115 snatch and 132 clean & jerk successful attempts with heaviest loads were choose to be studied. The statistical results show the relative MbHs for clean and jerk are 59.5% and 94.3% respectively, while in snatch the relative MbHs are 71.8%, 73.9%and 76.6% for 56 - 94, 105 and 105+ weight classes differently; the relative MbH (72.0%) of elite group (n=48) is lower than that (73.2%) of normal group (n=67) in snatch (p\u3c0.05)

A STUDY ON THE SPRINT START IN SHORT-TRACK SPEEDSKATING

INTRODUCTION: To a large extent, the sprint start in the 500-m short-track speed-skating event determines a successful performance. Therefore, it is anticipated that a study on the action in the sprint start would help to improve the outcome of the start. The aim of this study was to perform a kinematic analysis on some important factors that are related to a successful sprint start

One-Step Synthesis of Dynamically Shaped Stiff Nanorods Using Soft Silicone Materials to Control Water Repulsion and Collection

One-dimensional silicone nanostructures, such as filaments, wires, and tubes, have attracted significant attention, owing to their remarkable application capabilities in a large range of material and surface science. However, the soft mechanical properties of silicone cause vulnerability and irregularity in the synthesized structures, which limits their applications. Herein, a simple, solvent-free, and efficient dynamic Droplet Assisted Growth and Shaping (d-DAGS) strategy is proposed for the one-step synthesis and in situ control of the shape of silicone nanostructures. The special designed bamboo-shaped silicone nanorods (SNRs) that are produced by the repetitive dynamic regulation of growth conditions, concomitant with the periodic purging and injection of precursors, exhibit highly-regular and tunable structure with a specific number of segments, indicating that they can be tailor-made according to the requirements of various properties. The enhanced mechanical stiffness and chemical durability strongly support their excellent performances in water-resistance under both static and dynamic wetting conditions. The SNRs significantly promote buoyancy and self-cleaning properties; and exhibit very high water-harvesting efficiency compared with existing designs. Notably, the well-structured ultra-long rods with an ultrahigh aspect ratio (≈176) can also be fabricated by the d-DAGS method, and they can remain standing straight upwards and regular, even though they consist of flexible silicone

Silicone Nanofilament Coatings as Flexible Catalyst Supports for a Knoevenagel Condensation Reaction in Batch and Flow Systems

In this work, silicone nanofilament (SNF) coatings were prepared via a droplet-assisted growth and shaping (DAGS) approach, where the preparation of the coatings is allowed under ambient conditions. The application of SNF coatings as catalyst supports for amino moieties from (3-aminopropyl)triethoxysilane (APTES) was investigated. With the optimized coating conditions identified, the Brunauer–Emmett–Teller surface areas of a bare glass filter substrate and bare glass beads after the coating have increased by 5-fold and 16-fold, respectively. The SNF-coated filters were readily functionalized with amino groups via a liquid-phase deposition process, and their catalytic activities for a Knoevenagel reaction were evaluated using a batch reactor and a packed bed reactor. In both reactors, the as-prepared filters demonstrated superior catalytic performance over the functionalized filters without SNF coatings. Notably, the unique flexibility of the SNF coatings allowed the facile preparation of a packed bed reactor and a scalable catalytic system. It is expected that the packed bed system established in this study will support the development and the use of various SNF-supported organocatalysts and catalytic materials

Printable and Versatile Superhydrophobic Paper via Scalable Nonsolvent Armor Strategy

Despite great scientific and industrial interest in waterproof cellulosic paper, its real world application is hindered by complicated and costly fabrication processes, limitations in scale-up production, and use of organic solvents. Furthermore, simultaneously achieving nonwetting properties and printability on paper surfaces still remains a technical and chemical challenge. Herein, we demonstrate a nonsolvent strategy for scalable and fast fabrication of waterproofing paper through in situ surface engineering with polysilsesquioxane nanorods (PSNR). Excellent superhydrophobicity is attained on the functionalized paper surface with water contact angle above 160˚. Notably, the engineered paper features outstanding printability and writability, as well as greatly enhanced strength and integrity upon prolonged exposure to water (tensile strength ≈ 9.0 MPa). Additionally, the PSNR concurrently armors paper-based printed items and artwork with waterproofing, self-cleaning and antimicrobial functionalities without compromising their appearance, readability and mechanical properties. We also demonstrate that the engineered paper holds the additional advantages of easy processing, low cost and mechanochemical robustness, which makes it particularly promising for real world applications

A COMPARISON OF EMG AND KINEMATIC ANALYSIS BETWEEN GROUND AND TREADMILL RUNING FOR CHINESE ELITE SPRINTER-PU FAN FANG

Ms. Pu Fan-fang, a Chinese National championship, has been training on simulated treadmill for 4 years to improve her ability of velocity endurance. The purpose of the present study was to compare the changes of her movement structures in ground and treadmill running. EMG and' kinematical analysis were used in the test. The kinematical data results show that significant differences were noted between the two conditions for the take off angle, minimum knee angle of swing leg, the minimum angle between thigh and horizontal line, soar high and soar time. The EMG result revealed that the obvious differences of EMG distribution of eight muscles existed in the two conditions. According to the testing results, it should be considered that more using treadmill training could influence her movement structure although it is a good method to improve velocity endurance

Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields. However, their proficiency within specialized domains such as biomolecular studies remains limited. To address this challenge, we introduce Mol-Instructions, a meticulously curated, comprehensive instruction dataset expressly designed for the biomolecular realm. Mol-Instructions is composed of three pivotal components: molecule-oriented instructions, protein-oriented instructions, and biomolecular text instructions, each curated to enhance the understanding and prediction capabilities of LLMs concerning biomolecular features and behaviors. Through extensive instruction tuning experiments on the representative LLM, we underscore the potency of Mol-Instructions to enhance the adaptability and cognitive acuity of large models within the complex sphere of biomolecular studies, thereby promoting advancements in the biomolecular research community. Mol-Instructions is made publicly accessible for future research endeavors and will be subjected to continual updates for enhanced applicability.Comment: Project homepage: https://github.com/zjunlp/Mol-Instructions. Add quantitative evaluation

EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models

Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to the outdated/noisy data. To this end, many knowledge editing approaches for LLMs have emerged -- aiming to subtly inject/edit updated knowledge or adjust undesired behavior while minimizing the impact on unrelated inputs. Nevertheless, due to significant differences among various knowledge editing methods and the variations in task setups, there is no standard implementation framework available for the community, which hinders practitioners to apply knowledge editing to applications. To address these issues, we propose EasyEdit, an easy-to-use knowledge editing framework for LLMs. It supports various cutting-edge knowledge editing approaches and can be readily apply to many well-known LLMs such as T5, GPT-J, LlaMA, etc. Empirically, we report the knowledge editing results on LlaMA-2 with EasyEdit, demonstrating that knowledge editing surpasses traditional fine-tuning in terms of reliability and generalization. We have released the source code on GitHub at https://github.com/zjunlp/EasyEdit, along with Google Colab tutorials and comprehensive documentation for beginners to get started. Besides, we present an online system for real-time knowledge editing, and a demo video at http://knowlm.zjukg.cn/easyedit.mp4.Comment: The project website is https://github.com/zjunlp/EasyEdi