Hierarchical structures and magnetism of Co clusters: a perspective from integration of deep learning and a hybrid differential evolution algorithm.

Theoretically determining the lowest-energy structure of a cluster has been a persistent challenge due to the inherent difficulty in accurate description of its potential energy surface (PES) and the exponentially increasing number of local minima on the PES with the cluster size. In this work, density-functional theory (DFT) calculations of Co clusters were performed to construct a dataset for training deep neural networks to deduce a deep potential (DP) model with near-DFT accuracy while significantly reducing computational consumption comparable to classic empirical potentials. Leveraging the DP model, a high-efficiency hybrid differential evolution (HDE) algorithm was employed to search for the lowest-energy structures of CoN (N = 11-50) clusters. Our results revealed 38 of these clusters superior to those recorded in the Cambridge Cluster Database and identified diverse architectures of the clusters, evolving from layered structures for N = 11-27 to Marks decahedron-like structures for N = 28-42 and to icosahedron-like structures for N = 43-50. Subsequent analyses of the atomic arrangement, structural similarity, and growth pattern further verified their hierarchical structures. Meanwhile, several highly stable clusters, i.e., Co13, Co19, Co22, Co39, and Co43, were discovered by the energetic analyses. Furthermore, the magnetic stability of the clusters was verified, and a competition between the coordination number and bond length in affecting the magnetic moment was observed. Our study provides high-accuracy and high-efficiency prediction of the optimal structures of clusters and sheds light on the growth trend of Co clusters containing tens of atoms, contributing to advancing the global optimization algorithms for effective determination of cluster structures.

A mixed blessing for liver transplantation patients - Rapamycin.

BACKGROUND: Liver transplantation (LT) is an effective treatment option for end-stage liver disease. Mammalian target of rapamycin (mTOR) inhibitors, such as rapamycin, are widely used post LT. DATA SOURCES: In this review, we focused on the anti-cancer activities and metabolic side effects of rapamycin after LT. The literature available on PubMed for the period of January 1999-September 2022 was reviewed. The key words were rapamycin, sirolimus, liver transplantation, hepatocellular carcinoma, diabetes, and lipid metabolism disorder. RESULTS: Rapamycin has shown excellent effects and is safer than other immunosuppressive regimens. It has exhibited excellent anti-cancer activity and has the potential in preventing hepatocellular carcinoma (HCC) recurrence post LT. Rapamycin is closely related to two long-term complications after LT, diabetes and lipid metabolism disorders. CONCLUSIONS: Rapamycin prevents HCC recurrence post LT in some patients, but it also induces metabolic disorders. Reasonable use of rapamycin benefits the liver recipients.

Bidirectional Mediating Role of Loneliness in the Association Between Shyness and Generalized Pathological Internet Use in Chinese University Students: A Longitudinal Cross-Lagged Analysis.

This 1-year longitudinal study examined the bidirectional mediating role of loneliness in the association between shyness and generalized pathological Internet use (GPIU) in a sample of 291 Chinese university students (143 men, mean age = 19.07 years). A fully cross-lagged panel design was used in which shyness, loneliness, and GPIU were assessed at 3 time points separated by 6-month intervals (named T1, T2, and T3). The results indicated that relationships among shyness, loneliness, and GPIU were dynamic and bidirectional. Specifically, T1 shyness positively predicted increased T2 loneliness, T2 shyness positively predicted increased T3 loneliness, and T2 loneliness positively predicted increased T3 shyness. Additionally, T1 GPIU positively predicted increased T2 loneliness, T2 GPIU positively predicted increased T3 loneliness, and T2 loneliness positively predicted increased T3 GPIU. Loneliness was found to play a bidirectional mediating role in the association between shyness and GPIU. Specifically, T1 shyness and T3 GPIU were mediated through increased loneliness at T2, and T1 GPIU and T3 shyness were mediated through increased loneliness at T2. Furthermore, relationships among shyness, loneliness, and GPIU were the same across the 2 groups, with the strength of relationships being stronger for men.

Influence of Ongoing Task Difficulty and Motivation Level on Children's Prospective Memory in a Chinese Sample.

Prospective memory (PM) is the process associated with the task of realizing delayed intentions in the future. Researchers distinguish two types of PM, namely time-based PM (tbPM) and event-based PM (ebPM). Experiment 1 investigated the developmental trajectory of 3- to 5-year-old preschool children's PM ability, and the occurrence of delayed retrieval (children execute the PM task in a larger window of opportunity) in both tbPM and ebPM tasks. Results revealed that the 5-year-old children outperformed the 3- and 4-year-old children in PM. Moreover, delayed retrieval was more likely to occur in tbPM task than in ebPM task. In Experiment 2, the influence of ongoing task (OT) difficulty on PM performance was investigated with a sample of 5-year-old children. Results revealed no significant effect of OT difficulty on PM performance. In Experiment 3, we improved children's motivation level to complete the OT, then explored the influence of OT difficulty on children's PM performance. Results revealed that the effect of OT difficulty on PM performance became significant after increasing the children's motivation to complete the OT. These results provide insights into the mechanism of attentional resource allocation in PM tasks and have crucial educational and social implications.