An optimal aggregation method for interval grey numbers using on Steiner-Weber point with application

Aiming at the problem of low accuracy of two-dimensional preference information aggregation, this paper takes two-dimensional interval grey numbers as an example to define its preference information mapping rules. This rule maps preference information to preference points on a two-dimensional plane. Based on the theory of plane Steiner-Weber point, we construct a two-dimensional optimal model, and prove the optimality of the model theoretically. Then, adopt plant growth simulation algorithm (PGSA) to solve the proposed model. The obtained optimal aggregation point that can represent the comprehensive opinions. Finally, by analyzing the selection problem of Fangcang shelter hospital and comparing it with the particle swarm optimization (PSO) method, we conclude that the sum of weighted Euclidean distance obtained by our method is minimal. The aggregation precision of our method is higher than that of other aggregation method to a certain extent. © 2023 Elsevier Ltd

SA-FGDEM: A Self-adaptive E-Learning Performance Prediction Model

With the rapid development of computer computing power and the severe challenges brought by the COVID-19, e-learning, as the optimal solution for most students and other learner groups, plays an extremely important role in maintaining the normal operation of educational institutions. As the user community continues to expand, it has become increasingly important to guarantee the quality of teaching and learning. One way to ensure the quality of online education is to construct e-learning behavior data to build learning performance predictors. Still, most studies have ignored the intrinsic correlation between e-learning behaviors. Therefore, this study proposes an adaptive feature fusion-based e-learning performance prediction model (SA-FGDEM) relying on the theoretical model of learning behav-ior classification. The experimental results show that the feature space mined by fine-grained differential evolution algorithm and the adaptive feature fusion combined with differential evolution algorithm can support e-learning performance prediction more effectively and is better than the benchmark method. © 2022 IEEE.

Apatinib in combination with camrelizumab, a humanized immunoglobulin G4 monoclonal antibody against programmed cell death-1, in patients with metastatic acral melanoma

Background: Patients(pts) with metastatic acral melanoma respond poorly to anti-PD-1 monotherapy. Apatinib, a vascular endothelial growth factor (VEGF) inhibitor, is a kind of antiangiogenic drugs which have shown synergistic therapeutic effects in combination with PD-1 blockade. We conducted this single-center, open label phase trial to evaluate the safety and efficacy of camrelizumab in combination with apatinib in advanced treatment-naïve acral melanoma pts. Methods: Eligible participants were adult pts (aged 18 to 75) with histologically confirmed unresectable stage or distant metastatic acral melanoma. Exclusion criterion included unknown primary melanoma, brain metastatic disease or previous use of anti PD-1 ab. Pts received camrelizumab at 200mg intravenous infusion every 2 weeks, in combination with apatinib 250 mg orally once a day. The primary endpoint was ORR according to RECIST 1.1 criteria, and the secondary endpoints were safety and RFS. Results: Thirty pts were enrolled from April 2019 to January 2021. Basic characteristics: the mean age was 56.7 years, 22 pts were at stage, 33.3% had an elevated LDH level. Median tumor burden was 45mm (10-187). Gene mutation: Nras 4, cKit 3, Braf 2. Up to January 2021, 27 pts could be evaluated, in which 2 pts got CR, 4 pts achieved PR, and 63% experienced tumor shrinkage. The ORR and DCR were 22.2% and 77.8%, respectively. With a median follow up time of 8.3 months, the median PFS was 8.0 months (95% CI, 3.68, 10.19), the one-year durable response rate was 83.3% and the duration of response time was still not reached. Univariate analysis showed high LDH level was negatively associated with PFS. Whole exome data of baseline tumor biopsies revealed a positive correlation between high copy number variation (CNV) plus high mutational load (TMB) and efficacy, and all of the 4pts with MDC1 gene mutation got tumor shrink and 2 got PR. 96.7% pts experienced treatment-related AEs (TRAEs), including hand foot syndrome in 40%, proteinuria in 40%, liver dysfunction in 36.7%, and hypothyroidism in 30%. The grade 3-4 TRAEs were 33.3%. AE-related permanent discontinuation occurred in only 13.3% pts. 6 pts had delays of treatment due to the COVID-19 epidemic. No dose-limiting toxicities and suspected unexpected AEs were observed in the combination. Conclusions: The combination of apatinib plus camrelizumab was tolerable and showed promising antitumor activities and PFS improvement in pts with treatment-naïve metastatic acral melanoma. The survival is still in follow up.