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Supplementary Material 8

The encapsulation of catalytic active centers into polymer hydrogels represents a simple and effective strategy for enzyme mimicry. Current methods only enable the preparation of macroscopic enzyme carriers, which are far from natural enzymes in terms of their sizes, local chemical and physical properties, and catalytic activities. In this work, a nanogel strategy to immobilize hemin, a mimic of the active center for horseradish peroxidase (HRP), into a polyacrylamide (PAAm) matrix is demonstrated. Hemin was modified using N-(3-aminopropyl) methacrylamide hydrochloride (APMA) and the modified hemin together with excess APMA were covalently incorporated into PAAm nanogels. The resulting Hem@Gel shows enhanced catalytic activity and environmental tolerance compared with hemin and unmodified nanogel Hem/Gel, which has been demonstrated via the catalytic oxidation of various organic dyes. Further characterization and molecular simulations reveal the Fe–N coordination between the pendant groups and the enrichment of dye molecules and H2O2 in PAAm nanogels, which together enhance the local reaction rate and realize an overall improvement in catalytic efficiency.

Previous works on learning-based caching problems often only concern prefetching popular contents during off-peak traffic hours and service them to the edge at peak periods. In this letter, we investigate the cache strategy design problem with two possibly conflicting objectives in wireless networks when consumer preferences are unknown. We focus on caching for paid contents and model this decision making problem in a combinatorial multi-objective multi-armed bandit (CMO-MAB) perspective, by taking both the aggregated offloading traffic in dominant objective and the cumulative profit in non-dominant objective into account. Then, we propose the combinatorial scalarizated multi-objective upper confidence bound (CSMO-UCB) and the combinatorial Pareto multi-objective upper confidence bound (CPMO-UCB) algorithms, respectively, to jointly optimize total reward vectors in both objectives. Simulation results demonstrate that the proposed algorithms outperform their competitors, which are not specifically designed to address the caching problems involving dominant and non-dominant objectives.

Previous works on learning-based caching problems often only concern prefetching popular contents during off-peak traffic hours, and service them to the edge at peak periods. In this work, we investigate the cache strategy design problem with two possibly conflicting objectives in mobile edge networks when consumer preferences are unknown. We focus on caching for paid contents, and model the decision making problem in a combinatorial multi-objective multi-armed bandit (CMO-MAB) perspective, by taking both the aggregated offloading traffic data in dominant objective and the cumulative revenue in non-dominant objective into account. Furthermore, we propose a multi-objective proactive caching (MOPC) algorithm to jointly optimize the total reward vectors in both objectives. Simulation results demonstrate that the proposed MOPC algorithm outperforms its competitors, which are not specifically designed to address the caching problem involving dominant and non-dominant objectives.

Many synthetic routes have been explored to make small molecule sulfonimidamides (SIAs), however, its introduction into larger molecules such as oligopeptides has not been studied before. We herein demonstrate three alternative and complementary methods for synthesis of SIA based pseudopeptides, on solid phase, using both on and off‐resin SIA‐synthesis, via sulfonimidoyl chlorides from sulfonamides, in high conversion. Beside evaluation of various resins such as 2‐CTC, Wang, and Rink amide‐ChemMatrix, the possibilities to further N‐functionalize and cyclize the SIA functionality on solid support are shown. The diastereomers of SIA containing pseudopeptides could in most cases be separated using normal reverse phase preparative HPLC. The solid phase SIA methodology has many advantages when it comes to handling and purification as compared to in solution, and will therefore enable exploration of the SIA group as isosteric substitutions and peptidomimetic building blocks in the development of drug‐like pseudopeptides in many ways. Of particular note these approaches facilitate combinatorial library synthesis as demonstrated herein.