Current understanding of the longitudinal relationships between different aspects of peer relationships and mental health problems in early- to mid-adolescence is limited. In particular, the role played by gender in these developmental cascades processes is unclear, little is known about within-person effects between bullying victimization and internalizing symptoms, and the theorized benefits of friendship and social support are largely untested. Addressing these important research gaps, this study tested a number of theory-driven hypotheses (e.
View Article and Find Full Text PDFPrinting of large-area solar panels necessitates advanced organic solar cells with thick active layers. However, increasing the active layer thickness typically leads to a marked drop in the power conversion efficiency. Here we developed an organic semiconductor regulator, called AT-β2O, to tune the crystallization sequence of the components in active layers.
View Article and Find Full Text PDFIn clinical scenarios, bone defects stemming from trauma, infections, degenerative diseases, or hereditary conditions necessitate considerable bone grafts. Researchers ardently focus on creating diverse biomaterials to expedite and enhance these intricate restorative processes. These biomaterials play a pivotal role in aiding osteogenesis and angiogenesis factors for reconstructing stable, fully developed bone tissue.
View Article and Find Full Text PDFBackground: Dietary supplementation for beef cattle, using natural plant extracts, such as oregano essential oil (OEO), has proven effective in enhancing growth performance, beef production quantity and quality, and ensuring food safety. However, the precise mechanisms underlying these effects remain unclear. This study investigated the impact of OEO on carcass traits, muscle fiber structure, meat quality, oxidative status, flavor compounds, and gene regulatory mechanisms in the longissimus thoracis (LT) muscles of beef cattle.
View Article and Find Full Text PDFGraph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness in deep layers. Two key weaknesses of existing research on deep GNN models are: (1) ignoring the beneficial aspects of intra-class smoothing while focusing solely on reducing inter-class smoothing, and (2) inefficient computation of residual weights that neglect the influence of neighboring nodes' distributions. To address these weaknesses, we propose a novel Smoothing Deceleration (SD) strategy to reduce the smoothing speed rate of nodes as information propagates between layers, thereby mitigating over-smoothing.
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