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The slime mould algorithm (SMA), as an emerging and promising swarm intelligence algorithm, has been studied in various fields. However, SMA suffers from issues such as easily getting trapped in local optima and slow convergence, which pose challenges when applied to practical problems. Therefore, this study proposes an improved SMA, named HESMA, by incorporating the covariance matrix adaptation evolution strategy (CMA-ES) and storing the best position of each individual (SBP). On one hand, CMA-ES enhances the algorithm's local exploration capability, addressing the issue of the algorithm being unable to explore the vicinity of the optimal solution. On the other hand, SBP enhances the convergence speed of the algorithm and prevents it from diverging to other inferior solutions. Finally, to validate the effectiveness of our proposed algorithm, this study conducted experiments on 30 IEEE CEC 2017 benchmark functions and compared HESMA with 12 conventional metaheuristic algorithms. The results demonstrated that HESMA indeed achieved improvements over SMA. Furthermore, to highlight the performance of HESMA further, this study compared it with 13 advanced algorithms, and the results showed that HESMA outperformed these advanced algorithms significantly. Next, this study applied HESMA to five engineering optimization problems, and the experimental results revealed that HESMA exhibited significant advantages in solving real-world engineering optimization problems. These findings further support the effectiveness and practicality of our algorithm in addressing complex engineering design challenges. [ABSTRACT FROM AUTHOR]

Background: Undifferentiated small round-cell sarcomas (uSRCSs) are a subgroup of sarcomas that are difficult to diagnose. Some uSRCSs have specific gene re-arrangements, but others do not. Currently, there is no specific treatments for advanced uSRCSs, and its treatment is largely based on general experience with sarcomas, which includes chemotherapy, targeted therapy, and immunotherapy. In this article, we report a patient with uSRCS who responded to treatment with anti-VEGF inhibitor surufatinib and anti-PD-1 inhibitor camrelizumab after progression on first-line chemotherapy, second-line anlotinib combined with immunotherapy, and third-line chemotherapy., Case Description: In July 2020, a 37-year-old female patient was diagnosed with advanced uSRCS. Results for the Ewing sarcoma RNA binding protein 1 and Wilms tumor suppressor (EWSR1/WT1) fusion gene were negative. The patient was also negative with BCOR (BCL6 co-repressor) and CIC (capicua transcriptional repressor) fusion gene. The next-generation sequencing results revealed point mutations on Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Beta (PIK3CB), Transcription Factor Binding To IGHM Enhancer 3 (TFE3), Mucin 16 (MUC16), and AXL (Axl, also called UFO, ARK, and Tyro7, is part of a family of receptor tyrosine kinases). The patient received 4 cycles of the Ifosfamide and epirubicin hydrochloride regimen, and her best objective response was stable disease. On November 3, 2020, a computed tomography (CT) scan revealed progressive disease (PD). Two cycles of camrelizumab (a programmed death-1 inhibitor) plus anlotinib (an anti- vascular endothelial growth factor drug) were administered, but PD was again observed. Thus, a regimen of gemcitabine plus docetaxel was adopted. Unfortunately, the disease progressed once again after two cycles of the treatment. On February 4, 2021, the patient began to receive targeted therapy with surufatinib combined with camrelizumab. A CT scan showed that the tumor achieved a partial response. As of April 2023, the patient had a progression-free survival time of 26 months., Conclusions: Surufatinib in combination with camrelizumab could be effective in the treatment of advanced uSRCSs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Huang, Chen, Ye, Du, Voutsadakis, Seetharam, Zhang and Lu.)

We proposed a "Ni sacrifice" method to fabricate Al-based highly reflective p-electrode in the ultraviolet spectral region for AlGaN-based deep-ultraviolet light-emitting diodes (DUV-LEDs). The "Ni sacrifice" p-electrode could have a high optical reflectivity of around 90% at the DUV spectral region below 300 nm. Compared to Ni/Au, indium tin oxide (ITO), and Pd p-contacts, the "Ni sacrifice" led to a higher resistivity of p-contacts and a slightly higher operated voltage of the DUV-LEDs (within 0.6 V at 20 mA). Although the electrical performance was degraded slightly, the light output power and external quantum efficiency of the DUV-LEDs could be improved by utilizing the "Ni sacrifice" p-electrode. Besides, we introduced a grid of vias in the device mesa and reduced the diameter of the vias to achieve an enhanced peak external quantum efficiency (EQE) up to 1.73%. And the wall-plug efficiency (WPE) of DUV-LEDs with a "Ni sacrifice" p-electrode was higher than that of Ni/Au p-electrode DUV-LEDs at low currents. These results highlight the great potential of the proposed "Ni sacrifice" reflective p-electrode for use in DUV-LEDs.