Influence of data elements on China's agricultural green total factor productivity.

Exploring the effect and mechanism of data elements on agricultural green total factor productivity in China, has great significance for fully releasing the significant potential of data elements and promoting green agricultural development. Based on the panel data of China's 30 provinces from 2010 to 2022, this paper explored the fixed effects model to analyze the functional response of data elements on the agricultural green total factor productivity (AGTFP). The research finding shows that the data elements have significant promoting effects on the AGTFP, after a series of robustness and endogeneity tests.

Hybrid path planning algorithm for underactuated AUV based on RRT star and APF.

To address the kinematic constraints and real-time requirements of autonomous underwater vehicle (AUV), this paper proposes a novel path planning algorithm: Directional Cone and Goal-Biased Dynamic Artificial Potential Field RRT* (DCGB-DAPF-RRT*). The algorithm integrates four key techniques-Directional Cone sampling, Goal-Biased sampling, Adaptive Step Length, and a Dynamic Artificial Potential Field-to improve sampling efficiency and path quality over conventional RRT-based methods. In addition, redundant node pruning and cubic non-uniform B-spline interpolation are employed to enhance trajectory smoothness and ensure kinematic feasibility.

Effects of physical training programs on healthy badminton players' performance: a systematic review and meta-analysis.

Research Background: Despite the abundance of common physical training programs designed for healthy badminton players, there is a significant gap in comprehensive studies evaluating their impact on player performance.

Research Purpose: This systematic review and meta-analysis aimed to determine the effects of common physical training programs on performance outcomes of healthy badminton players.

Method: To address this gap, a meticulous search was conducted across several databases, including Scopus, PubMed, Web of Science, and EBSCOhost, up until January 2024, leading to the selection of relevant articles for a systematic review and subsequent meta-analysis using Review Manager (version 6) software.

HYFF-CB: Hybrid Feature Fusion Visual Model for Cargo Boxes.

In automatic loading and unloading systems, it is crucial to accurately detect the locations of boxes inside trucks in real time. However, the existing methods for box detection have multiple shortcomings, and can hardly meet the strict requirements of actual production. When the truck environment is complex, the currently common models based on convolutional neural networks show certain limitations in the practical application of box detection.

Particle displacement refinement based on hybrid cross-correlation optical flow method with gradient constancy assumption.

In particle image velocimetry (PIV), the brightness of a particle image sequence may change due to uneven laser intensity distribution and fluctuations in laser output. Consequently, the optical flow method (OFM), which relies on the brightness constancy assumption, becomes unsuitable. The traditional variational OFM is only accurate for small displacement fields but lacks robustness and accuracy when applied to PIV images with intensity variations.

Interventional effect of core stability training on pain and muscle function of youth with chronic non-specific lower back pain: A randomized controlled trial.

Nowadays, due to lifestyle changes, the number of young people suffering from chronic non-specific low back pain (CNLBP) is gradually increasing. The recent guidelines for the treatment of low back pain emphasize that exercise therapy is the preferred treatment method for CNLBP. This study take ordinary college male students with CNLBP as objective of the study, focused into how core stability training affected the pain and muscle function of the CNLBP of youth.

Carboxyl-functionalized covalent organic frameworks for the extraction of malachite green and crystal violet in environmental water samples prior to quantification by high-performance liquid chromatography.

In this study, monodisperse, uniform, and spherical covalent organic frameworks (COFs) were synthesized using 1,3,5-tris (4-aminophenyl) benzene and 1,3,5-tricarboxaldehyde benzene at room temperature. Post-modification of 6-aminocaproic acid on the COFs yielded carboxyl-modified COFs (COFs-COOH). The modification enhanced the hydrophilicity and adsorption efficiencies of COFs-COOH for malachite green (MG) and crystal violet (CV).

Arthroscopic Surgery Combined With Platelet-Rich Plasma Does Not Significantly Improve Pain, Function, Complications, and Retear Rate Compared With Arthroscopic Surgery Alone for Full-Thickness Rotator Cuff Tears: A Systematic Review and Meta-analysis.

Purpose: To evaluate the effectiveness and safety of arthroscopic surgery combined with platelet-rich plasma (PRP) compared with arthroscopic surgery alone in the treatment of patients with full-thickness rotator cuff tears.

Methods: The Cochrane Library, PubMed, Embase, Scopus, EBSCO, Web of Science, China National Knowledge Infrastructure, and Wanfang Database were systematically searched from inception to November 2023. Subject words combined with free words were used to collect randomized controlled trials focusing on arthroscopic surgery combined with PRP in the treatment of full-thickness rotator cuff tears.

Controllable synthesis of uniform flower-shaped covalent organic framework microspheres as absorbent for solid-phase extraction of trace 2,4-dichlorophenol.

Controllable synthesis of micro-flower covalent organic frameworks (MFCOFs) with controllable size, monodisperse, spherical, and beautiful flower shape was realized by using 2,5-diformylfuran (DFF) and p-phenylenediamine (p-PDA) as building blocks at room temperature. High-quality MFCOFs (5 - 7 μm) were synthesized by controlling the kind of solvent, amounts of monomers, catalyst content, and reaction time. The synthesized MFCOFs possessed uniform mesopores deriving from the intrinsic pores of frameworks and wide-distributed pores belonging to the gap between the petals.

Magnetic porous carbon material derived from imine-linked covalent organic frameworks for magnetic solid phase extraction of trace chlorine-containing herbicides in soil.

Here, imine-linked covalent organic frameworks coated FeO microspheres were fabricated and employed as the self-template to prepare magnetic porous carbon material. The magnetic solid phase extraction (MSPE) performance of such magnetic covalent organic frameworks derived porous carbons (CMCOFs) were studied for the first time, and the improved MSPE performance was verified. The variations of chemical and material properties in the carbonization processes were studied, and it was found that the CMCOFs carbonated at 400°C exhibited highest adsorption efficiencies for chlorine-containing herbicides due to the formation of nitrile components at this stage.

Effect of Social-Psychological Intervention on Self-Efficacy, Social Adaptability and Quality of Life of Internet-Addicted Teenagers.

Background: Internet addiction leads to psychological and social damage to teenagers. Rehabilitation treatment of Internet-addicted adolescents has aroused widespread concern. This study aims to explore the effect of social-psychological intervention on self-efficacy, social adaptability, and quality of life of Internet-addicted teenagers.

Analysis of the Influence of Outward Bound Training Based on Data Analysis in College Physical Training.

The competition for talents in the modern society is constantly intensifying. College students not only have good physical and psychological quality but also bear hardships and stand hard work and adapt to the fast-paced working environment in order to adapt to the development of the times. With the advent of the era of big data, advanced technology has been applied to physical exercise and development, providing opportunities and challenges for the development of sports.

Early Detection of College Students' Psychological Problems Based on Decision Tree Model.

The paper starts with the research on the early discovery of college students' psychological problems. Besides, it analyzes the data of the general survey of college students' mental health in a certain university, the existing data of students with psychological problems, and the questionnaire data of students' basic information in school. By comprehensively using the decision tree model and Kendall correlation analysis and other methods, using Python and SPSS software to preprocess the data and realize the model, it can obtain a psychological problem prediction model based on the objective behavior data of college students.