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With the increasing application of Combined Heat and Power (CHP) units, Combined Heat and Power Economic Dispatch (CHPED) has emerged as a significant issue in power system operations. To address the complex CHPED problem, this paper proposes an effective economic dispatch method based on the Improved Artificial Hummingbird Algorithm (IAHA). Given the complex constraints of the CHPED problem and the presence of valve point effects and prohibited operating zones, it requires the algorithm to have high traversal capability in the solution space and be resistant to becoming trapped in local optima. IAHA has introduced two key improvements based on the characteristics of the CHPED problem and the shortcomings of the standard Artificial Hummingbird Algorithm (AHA). Firstly, IAHA uses chaotic mapping to initialize the initial population, enhancing the algorithm’s traversal capability. Second, the guided foraging of the standard AHA has been modified to enhance the algorithm’s ability to escape from local optima. Simulation experiments were conducted on CHP systems at three different scales: 7 units, 24 units, and 48 units. Compared to other algorithms reported in the literature, the IAHA algorithm reduces the cost in the three testing systems by up to USD 18.04, 232.7894, and 870.7461. Compared to other swarm intelligence algorithms reported in the literature, the IAHA algorithm demonstrates significant advantages in terms of convergence accuracy and convergence speed. These results confirm that the IAHA algorithm is effective in solving the CHPED problem while overcoming the limitations of the standard AHA.

The transplantation of GABAergic neuron cells has been reported to alleviate nerve pain and improve motor function after spinal cord injury (SCI). However, human mesenchymal stem cell (hMSC) differentiation into GABAergic neuron cells in a sufficient quantity remains to be accomplished. From a database screening, cAMP-responsive element-binding protein 1 (CREB1) was chosen as a potential modulator due to its critical role in the protein–protein interaction of genes related to GABAergic neural differentiation. Here, CREB1 was overexpressed in transfected hMSCs, where CREB1 could induce differentiation into GABAergic neuron cells with an upregulation of Map2 and GAD1 by 2- and 3.4-fold, respectively. Additionally, GABAergic neural differentiation was enhanced, while Notch signaling was inhibited, and BRN2 transcriptional activation played an important role in neuronal maturation. Moreover, transfected hMSCs injected into immunocompromised mice caused by CsA exhibited the neuronal markers Tuj1 and Map2 via the intraspinal route, suggesting an improvement in survival and neural differentiation. Significantly, improvement in both BMS scores (6.2 ± 1.30 vs. 4 ± 0) and thermal hyperalgesia latency (7.74 ± 2.36 s vs. 4.52 ± 0.39 s) was seen compared with the SCI naïve treatment at 4 weeks post-transplantation. Our study demonstrates that CREB1 is crucial in generating induced GABAergic neuron cells (iGNs) originating from hMSCs. Transplanting iGNs to injured spinal cord provides a promising strategy for alleviating neuropathic pain and locomotion recovery after SCI.

The flexible job shop scheduling problem (FJSP) is of great importance for realistic manufacturing, and the problem has been proven to be NP-hard (non-deterministic polynomial time) because of its high computational complexity. To optimize makespan and critical machine load of FJSP, a discrete improved grey wolf optimization (DIGWO) algorithm is proposed. Firstly, combined with the random Tent chaotic mapping strategy and heuristic rules, a hybrid initialization strategy is presented to improve the quality of the original population. Secondly, a discrete grey wolf update operator (DGUO) is designed by discretizing the hunting process of grey wolf optimization so that the algorithm can solve FJSP effectively. Finally, an adaptive convergence factor is introduced to improve the global search ability of the algorithm. Thirty-five international benchmark problems as well as twelve large-scale FJSPs are used to test the performance of the proposed DIGWO. Compared with the optimization algorithms proposed in recent literature, DIGWO shows better solution accuracy and convergence performance in FJSPs at different scales.

HIV-associated neurocognitive disorder (HAND) is an array of neurocognitive changes associated with HIV infection, and the roles of microRNAs in HAND have not yet been completely revealed. Based on published data and publicly available databases, we constructed an integrated miRNA-mRNA network involved in HAND. Bioinformatics analyses, including gene ontology, network analysis, and KEGG pathway analysis, were applied for further study of the network and the genes of the network. The axon guidance KEGG pathway, three genes NTNG1, EFNB2, CXCL12, and 17 miRNAs which regulate these genes are spotlighted in our study. This study provides new perspectives to the knowledge of miRNAs’ roles in the progression of HAND, and our findings provide potential therapeutic targets and clues of HAND.