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Hydrogels have emerged as promising candidates for flexible devices and water resource management. However, further applications of conventional hydrogels are restricted due to their limited performance and lack of a recycling strategy. Herein, a tough, flexible, and recyclable hydrogel sensor via a visible-light-triggered polymerization is rapidly created. The Zn2+ crosslinked terpolymer is in situ polymerized using g-C3N4 as the sole initiator to form in situ chain entanglements, endowing the hydrogels with low hysteresis and high elasticity. In the use phase, the hydrogel sensor exhibited high ion conductivity, excellent mechanical properties, fast responsiveness, high sensitivity, and remarkable anti-fatigue ability, making it exceptionally effective in accurately monitoring complex human movements. At the end-of-life (EOL), leveraging the synergy between the photodegradation capacity of g-C3N4 and the adsorption function of the hydrogel matrix, the post-consumer hydrogel is converted into water remediation materials, which not only promoted the rapid degradation of organic pollutants, but also facilitated collection and reuse. This innovative strategy combined in situ entangling reinforcement and tailored recycle-by-design that employed g-C3N4 as key blocks in the hydrogel to achieve high performance in the use phase and close the loop through the reutilization at EOL, highlighting the cost-effective synthesis, specialized structure, and life cycle management.
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In order to investigate the effects of a flag rugby game programs on the development of gross motor skills and physical fitness in 5-6 year old preschool children. An overall random sampling method was adopted to select 56 preschoolers aged 5-6 years from class A and class B,class A was the ExG (28) implemented a flag rugby games intervention program,and class B was the ConG (28) implemented a regular physical education program,with a 12-week intervention period.The content and requirements of the experimental intervention program were determined through a systematic analysis method, and the subjects' gross motor skills level was tested using the TGMD-3, and their physical fitness level was measured using China's fifth national physical fitness monitoring of early childhood (3-6 years) component.Experimental data were statistically analyzed using independent samples t-test, paired samples t-test, and repeated measures ANOVA test.After 12 weeks of practice, 1ï¼We found that the ExG outperformed the ConG in Skip,One hand stationary dribble, Overhand throw, Underhand throw, Forehand strike of self-bounced,Kick a stationary ball, Total object control subject score, Total gross motor score test results with significant differences (p < 0.05).The ExG differed significantly (p < 0.01) in Grip strength, Stand long jump,Sit forward bend, Continuous jump on both feet,15 m obstacle run,Walk the balance beam, while the ConG differed significantly (p < 0.05) only in Continuous jump on both feet,15 m obstacle run and Stand long jump.2ï¼We also found gender differences in gross motor skills and Physical fitness test results, this difference is manifested in boys outperformed girls in Total object control subject Score, Grip strength and 15 m obstacle run with significant difference (p < 0.05), girls outperformed boys in Sit forward bend with significant difference (p < 0.05).The 12-week flag rugby game programs improved gross motor skills and physical fitness levels of 5-6 year old preschoolers more comprehensively than the regular program, and we recommend the purposeful and organized promotion of a flag rugby game programs in the physical activity curriculum for 5-6 year old preschoolers.
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BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. The accurate survival prediction for CRC patients plays a significant role in the formulation of treatment strategies. Recently, machine learning and deep learning approaches have been increasingly applied in cancer survival prediction. However, most existing methods inadequately represent and leverage the dependencies among features and fail to sufficiently mine and utilize the comorbidity patterns of CRC. To address these issues, we propose a self-attention-based graph learning (SAGL) framework to improve the postoperative cancer-specific survival prediction for CRC patients. METHODS: We present a novel method for constructing dependency graph (DG) to reflect two types of dependencies including comorbidity-comorbidity dependencies and the dependencies between features related to patient characteristics and cancer treatments. This graph is subsequently refined by a disease comorbidity network, which offers a holistic view of comorbidity patterns of CRC. A DG-guided self-attention mechanism is proposed to unearth novel dependencies beyond what DG offers, thus augmenting CRC survival prediction. Finally, each patient will be represented, and these representations will be used for survival prediction. RESULTS: The experimental results show that SAGL outperforms state-of-the-art methods on a real-world dataset, with the receiver operating characteristic curve for 3- and 5-year survival prediction achieving 0.849±0.002 and 0.895±0.005, respectively. In addition, the comparison results with different graph neural network-based variants demonstrate the advantages of our DG-guided self-attention graph learning framework. CONCLUSIONS: Our study reveals that the potential of the DG-guided self-attention in optimizing feature graph learning which can improve the performance of CRC survival prediction.
Assuntos
Neoplasias Colorretais , Aprendizado de Máquina , Humanos , Redes Neurais de Computação , Período Pós-Operatório , Curva ROCRESUMO
The configuration of asymmetric supercapacitors (ASCs) has proven to be an effective approach to increase the energy storage properties due to the expanded working voltage resulting from the well-separated potential windows of the cathode and anode. However, carbonaceous anode materials generally suffer from relatively low capacitance, which restricts the enhancement of the energy storage performance of the full device in a traditional asymmetrical design. Herein, a rational design of all-pseudocapacitive ASCs (APASCs) using pseudocapacitive materials with a novel hierarchical nanostructure on both electrodes was developed to optimize the electrochemical properties for high-performance ASC devices. The assembled APASC employed the MnO2/PPy nanocomposites covered MnOOH nanowire arrays with core-shell hierarchical architecture as the cathode and Fe2O3/PPy hybrid nanosheets with 3D porous network-like structure as the anode. Owing to the coordinated pseudocapacitive properties and unique hierarchical nanostructures, this assembled APASC exhibited an exceptional volumetric capacitance of 4.92F cm-3 in a stable voltage window of 2 V, a maximum volumetric energy density of 2.66 mWh cm-3 at 19.72 mW cm-3, and excellent cyclic stability over 10,000 cycles (90.6 % capacitance retention), as well as remarkable flexibility and mechanical stability, providing insights for the design of flexible energy storage systems with enhanced performance.
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The construction of binder-free electrodes with well-defined three-dimensional (3D) morphology and optimized electronic structure represents an efficient strategy for the design of high-performance electrocatalysts for the development of efficient green hydrogen technologies. Herein, Ru nanocrystals were modified on 3D interconnected porous FeOOH nanostructures with open network-like frameworks on NiFe foam (Ru/FeOOH@NFF), which were used as an efficient electrocatalyst. In this study, a 3D interconnected porous FeOOH with an open network structure was first electrodeposited on NiFe foam and served as the support for the in-situ modification of Ru nanocrystals. Subsequently, the Ru nanocrystals and abundant oxygen vacancies were simultaneously incorporated into the FeOOH matrix via the adsorption-reduction method, which involved NaBH4 reduction. The Ru/FeOOH@NFF electrocatalyst shows a large specific surface area, abundant oxygen vacancies, and modulated electronic structure, which collectively result in a significant enhancement of catalytic properties with respect to the oxygen evolution reaction (OER) and urea oxidation reaction (UOR). The Ru/FeOOH@NFF catalyst exhibits an outstanding OER performance, requiring a low overpotential (360 mV) at 200 mA cm-2 with a small Tafel slope (58 mV dec-1). Meanwhile, the Ru/FeOOH@NFF catalyst demonstrates more efficient UOR activity for achieving 200 mA cm-2 at a lower overpotential of 272 mV. Furthermore, an overall urea electrolysis cell using the Ru/FeOOH@NFF as the anode and Pt as the cathode (Ru/FeOOH@NFF||Pt) reveals a cell voltage of 1.478 V at 10 mA cm-2 and a prominent durability (120 h at 50 mA cm-2). This work will provide a valuable understanding of the construction of high-performance electrocatalysts with 3D microstructure for promoting urea-assisted water electrolysis.
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Confronting the pressing challenge of freshwater scarcity, polymeric membrane-based water treatment technology has emerged as an essential and effective approach. Poly(arylene ether)s (PAEs) polymers, a class of high-performance engineering thermoplastics, have garnered attention in recent decades as promising membrane materials for advanced water treatment approaches. The PAE-Based membranes are employed to resist the shortages of most common polymeric membranes, such as chemical instability, structural damage, membrane fouling, and shortened lifespan when deployed in harsh environments, owing to their excellent comprehensive performance. This article presents the advancements in the research of several typical PAEs, including poly(ether ether ketone) (PEEK), polyethersulfone (PES), and poly(arylene ether nitrile) (PEN). Techniques for membrane formation, modification strategies, and applications in water treatment have been reviewed. The applications encompass processes for oil/water separation, desalination, and wastewater treatment, which involve the removal of heavy metal ions, dyes, oils, and other organic pollutants. The commendable performance of these membranes has been summarized in terms of corrosion resistance, high-temperature resistance, anti-fouling properties, and durability in challenging environments. In addition, several recommendations for further research aimed at developing efficient and robust PAE-based membranes are proposed.