Time duration of post-activation performance enhancement (PAPE) in elite male sprinters with different strength levels

(1) Purpose: This study aimed to explore the time duration of post-activation performance enhancement (PAPE) in elite male sprinters with different strength levels. (2) Methods: Thirteen elite male sprinters were divided into a strong group (relative strength: 1RM squat normalized by body mass of ≥ 2.5; n = 6) and a weak group (relative strength of < 2.5; n =7). All sprinters performed one static squat jump (SSJ) at baseline and 15 s, 3 min, 6 min, 9 min, and 12 min following an exercise protocol including three reps of a 90% 1RM back squat. Two force plates were used to determine the vertical jump height, the impulse output, and the power output for all SSJs. (3) Results: Significant improvements in vertical jump height and peak impulse were observed (p < 0.05) at 3, 6, and 9 min, without significant between-group differences. The peak power had a significant increase in 3 min (p < 0.01) and 6 min (p < 0.05), with also no significant difference between-group differences. Moreover, the stronger subjects induced a greater PAPE effect than the weaker counterparts at 3, 6, and 9 min after the intervention. The maximal benefit following the intervention occurred at 6 min and 3 min after the intervention in the stronger and weaker subjects, respectively. (4) Conclusions: The findings indicated that three reps of a 90% 1RM back squat augmented the subsequent explosive movement (SSJ) for 3–9 min in elite male sprinters, especially in stronger sprinters.info:eu-repo/semantics/publishedVersio

Cytotoxic 13,28 Epoxy Bridged Oleanane-Type Triterpenoid Saponins from the Roots of <i>Ardisia crispa</i>

Ardisiacrispin D–F (1–3), three new 13,28 epoxy bridged oleanane-type triterpenoid saponins, together with four known analogues (4–7) were isolated from the roots of Ardisia crispa. The structures of 1–7 were elucidated based on 1D and 2D-NMR experiments and by comparing their spectroscopic data with values from the published literatures. Ardisiacrispin D–F (1–3) are first examples that the monosaccharide directly linked to aglycone C-3 of triterpenoid saponins in genus Ardisia are non-arabinopyranose. In the present paper, all compounds are evaluated for the cytotoxicity against three cancer cell lines (HeLa, HepG2 and U87 MG) in vitro. The results show that compounds 1, 4 and 6 exhibited significant cytotoxicity against Hela and U87 MG cells with IC50 values in the range of 2.2 ± 0.6 to 9.5 ± 1.8 µM. The present investigation suggests that roots of A. crispa could be a potential source of natural anti-tumor agents and their triterpenoid saponins might be responsible for cytotoxicity

GC-MLP: Graph Convolution MLP for Point Cloud Analysis

With the objective of addressing the problem of the fixed convolutional kernel of a standard convolution neural network and the isotropy of features making 3D point cloud data ineffective in feature learning, this paper proposes a point cloud processing method based on graph convolution multilayer perceptron, named GC-MLP. Unlike traditional local aggregation operations, the algorithm generates an adaptive kernel through the dynamic learning features of points, so that it can dynamically adapt to the structure of the object, i.e., the algorithm first adaptively assigns different weights to adjacent points according to the different relationships between the different points captured. Furthermore, local information interaction is then performed with the convolutional layers through a weight-sharing multilayer perceptron. Experimental results show that, under different task benchmark datasets (including ModelNet40 dataset, ShapeNet Part dataset, S3DIS dataset), our proposed algorithm achieves state-of-the-art for both point cloud classification and segmentation tasks

Longitudinal patterns of fish assemblages in relation to environmental factors in the Anning River, China

In order to explore the spatial layout of fish assemblages and their related environmental factors, a survey of species composition was conducted in the Anning River. From 2018 to 2021, 28 sites at 987–2,077 m in altitude were surveyed, gathering 64 species in total, of which 60 were native and 4 were exotic. Fifteen of the species sampled were indigenous to the upper Yangtze River, and two were classified as critically endangered or endangered. Fish communities displayed significant upstream-to-downstream variation. There are two site-groups, one covering upstream and tributaries and the other covering midstream and downstream. The upstream-tributary fish assemblages had a dominance of Nemacheilidae and Schizothoracinae, which are plateau species with habitat preferences for boulders and fast-flowing water. Conversely, the mid-downstream fish assemblages had a dominance of Gobioninae, Cyprininae, Bagridae and Siluridae, which are common river species that prefer slow-flowing water. The spatial patterns of these fish communities were chiefly affected by altitude and substratum composition. The fish assemblage pattern was consistent with the zonation concept because the fish communities changed abruptly and clearly along the upstream–downstream axis. The findings of this study offer a crucial research foundation for comprehending the fish assemblages of mountainous rivers, which will be conducive to biodiversity management and habitat preservation of aquatic species

Analyzing APIs documentation and code to detect directive defects

Application Programming Interface (API) documents represent one of the most important references for API users. However, it is frequently reported that the documentation is inconsistent with the source code and deviates from the API itself. Such inconsistencies in the documents inevitably confuse the API users hampering considerably their API comprehension and the quality of software built from such APIs. In this paper, we propose an automated approach to detect defects of API documents by leveraging techniques from program comprehension and natural language processing. Particularly, we focus on the directives of the API documents which are related to parameter constraints and exception throwing declarations. A first-order logic based constraint solver is employed to detect such defects based on the obtained analysis results. We evaluate our approach on parts of well documented JDK 1.8 APIs. Experiment results show that, out of around 2000 API usage constraints, our approach can detect 1158 defective document directives, with a precision rate of 81.6%, and a recall rate of 82.0%, which demonstrates its practical feasibility

Wearable respiration monitoring using an in-line few-mode fiber Mach-Zehnder interferometric sensor.

Continuous respiratory monitoring is extensively important in clinical applications. To effectively assess respiration rate (RR), tidal volume (TV), and minute ventilation (MV), we propose and experimentally demonstrate a respiration monitoring system using an in-line few-mode fiber Mach-Zehnder interferometer (FMF-MZI), which is the first to introduce in-line MZI into an optimal wearable design for respiration rate and volume monitoring. The optimal linear region of the proposed sensor is analyzed and positioned by a flexible arch structure with curvature sensitivity up to 8.53 dB/

Tensor Program Optimization with Probabilistic Programs

Automatic optimization for tensor programs becomes increasingly important as we deploy deep learning in various environments, and efficient optimization relies on a rich search space and effective search. Most existing efforts adopt a search space which lacks the ability to efficiently enable domain experts to grow the search space. This paper introduces MetaSchedule, a domain-specific probabilistic programming language abstraction to construct a rich search space of tensor programs. Our abstraction allows domain experts to analyze the program, and easily propose stochastic choices in a modular way to compose program transformation accordingly. We also build an end-to-end learning-driven framework to find an optimized program for a given search space. Experimental results show that MetaSchedule can cover the search space used in the state-of-the-art tensor program optimization frameworks in a modular way. Additionally, it empowers domain experts to conveniently grow the search space and modularly enhance the system, which brings 48% speedup on end-to-end deep learning workloads

Pd-CuFe Catalyst for Transfer Hydrogenation of Nitriles: Controllable Selectivity to Primary Amines and Secondary Amines

Summary: A multicomponent nanocatalyst system was fabricated for the transfer hydrogenation of nitrile compounds. This catalyst system contains palladium, copper, and iron, which are supported on the magnetite nanospheres, and the loading of palladium could be at the parts per million level. Palladium and copper contribute to the transformation of nitrile, and the product distribution highly depends on the alloying of Fe to Cu. The nitriles could be converted to primary amine by the Pd-Cu catalyst in the absence of Fe, whereas in the presence of Fe the products are secondary amines with high selectivity. This could be attributed to the electronic modulation of iron to copper. A variety of nitriles have been transformed to the corresponding primary or secondary amines with high selectivity, and the TOF reaches 2,929 hr−1 for Pd. Furthermore, the catalyst could be recycled by an external magnetic field and reused five times without severe activity loss. : Chemistry; Catalysis; Organic Chemistry Subject Areas: Chemistry, Catalysis, Organic Chemistr