Dynamic sub-route-based self-adaptive beam search Q-learning algorithm for traveling salesman problem.

In this paper, a dynamic sub-route-based self-adaptive beam search Q-learning (DSRABSQL) algorithm is proposed that provides a reinforcement learning (RL) framework combined with local search to solve the traveling salesman problem (TSP). DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive ε-beam search strategy, and a new Q-value update formula. Then, a self-adaptive beam search Q-learning (ABSQL) algorithm is designed. To solve the problem that the sub-route is not fully optimized in the ABSQL algorithm, a dynamic sub-route optimization strategy is introduced outside the QL framework, and then the DSRABSQL algorithm is designed. Experiments are conducted to compare QL, ABSQL, DSRABSQL, our previously proposed variable neighborhood discrete whale optimization algorithm, and two advanced reinforcement learning algorithms. The experimental results show that DSRABSQL significantly outperforms the other algorithms. In addition, two groups of algorithms are designed based on the QL and DSRABSQL algorithms to test the effectiveness of the five strategies. From the experimental results, it can be found that the dynamic sub-route optimization strategy and self-adaptive ε-beam search strategy contribute the most for small-, medium-, and large-scale instances. At the same time, collaboration exists between the four strategies within the QL framework, which increases with the expansion of the instance scale.

OsINV3 and Its Homolog, OsINV2, Control Grain Size in Rice.

Vacuolar invertase is involved in sugar metabolism and plays a crucial role in plant growth and development, thus regulating seed size. However, information linking vacuolar invertase and seed size in rice is limited. Here we characterized a small grain mutant sg2 (grain size on chromosome 2) that showed a reduced in grain size and 1000-grain weight compared to the wild type. Map-based cloning and genetic complementation showed that OsINV3 is responsible for the observed phenotype. Loss-of-function of OsINV3 resulted in grains of smaller size when compared to the wild type, while overexpression showed increased grain size. We also obtained a T-DNA insertion mutant of OsINV2, which is a homolog of OsINV3 and generated double knockout (KO) mutants of OsINV2 and OsINV3 using CRISPR/Cas9. Genetic data showed that OsINV2, that has no effect on grain size by itself, reduces grain length and width in the absence of OsINV3. Altered sugar content with increased sucrose and decreased hexose levels, as well as changes vacuolar invertase activities and starch constitution in INV3KO, INV2KO, INV3KOINV2KO mutants indicate that OsINV2 and OsINV3 affect sucrose metabolism in sink organs. In summary, we identified OsINV3 as a positive regulator of grain size in rice, and while OsINV2 has no function on grain size by itself. In the absence of OsINV3, it is possible to detect a role of OsINV2 in the regulation of grain size. Both OsINV3 and OsINV2 are involved in sucrose metabolism, and thus regulate grain size. Our findings increase our understanding of the role of OsINV3 and its homolog, OsINV2, in grain size development and also suggest a potential strategy to improve grain yield in rice.

Linear Supramolecular Polymers via Connecting Telechelic Polycaprolactone through Alkynylplatinum(II) Terpyridine Molecular Tweezer/Pyrene Recognition Motif.

By anchoring alkynylplatinum(II) terpyridine molecular tweezer/pyrene recognition motif on the chain-ends of telechelic polycaprolactone, high-molecular-weight supramolecular polymers have been successfully constructed via noncovalent chain extension, which demonstrate fascinating rheological and thermal properties. Moreover, the resulting assemblies exhibit interesting temperature- and solvent-responsive behaviors, which are promising for the development of adaptive functional materials.