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Diabetes mellitus represents a significant global health threat characterized by hyperglycemia caused by inadequate insulin secretion and/or insulin resistance. Exogenous insulin supplements had been recognized as a crucial treatment for achieving successful glycemic control in patients with Type 1 and most patients with Type 2 diabetes. Over the past century, substantial progress has been made in the development of novel insulin formulations, including the super‐fast‐acting and long‐acting basal insulin analogs, of which the latter is indispensable for the management of nocturnal fasting and intraprandial blood glucose within the normal physiological range. Recently, combining chemical and genetic engineering with drug optimization have resulted in a formidable evolution in ultra‐long‐acting weekly insulin. Here, the current state of once‐weekly insulin analogs and the euglycemic clamp technique used in the early clinical development to elucidate the pharmacokinetics and pharmacodynamics of this type of novel weekly insulin analogs were systematically overviewed. [ABSTRACT FROM AUTHOR]

Drastically lowering the usage of platinum while enhancing activity and stability toward oxygen reduction is critical to promoting energy conversion efficiency in metal‐air batteries. Herein, an efficient oxygen reduction catalyst was rationally designed by constructing ultrasmall Pt and Pt/MoC dual active sites co‐anchored on nitrogen‐doped carbon. Owing to the synergistic effect of the dual active sites, the optimized Pt‐MoC@NC delivers superior oxygen reduction activity with ultralow Pt loading. Especially, the Pt‐MoC@NC shows robust methanol tolerance. As the cathodic catalyst, Pt‐MoC@NC based zinc‐air battery possesses outstanding performance with a large peak power density of 100 mW cm−2 and long charge‐discharge durability. [ABSTRACT FROM AUTHOR]

Due to its properties (stable, affordable and non‐toxic), titanium dioxide (TiO2) has a promising future as electrode material for sodium‐ion batteries (SIBs). Its Na+ insertion/deinsertion mechanism, on the other hand, results in poor electronic conductivity and sluggish ionic diffusivity, leading to rapid capacity fading. Herein, a molten salt method is employed to creat abundant carbon pores framework, being capable of supporting plentiful ultra‐fine TiO2 adhering (U‐TiO2/C). With this unique porous structure of lots of exposed active sites, the U‐TiO2/C composite provides a faster ions transport and volume expansion buffer zone during cycling. As anode for SIBs, the U‐TiO2/C manifests splendid electrochemical performance. Specifically, the U‐TiO2/C electrode delivers a high capacity of 202.7 mAh g−1 after 100 cycles at 0.1 A g−1 and 91.4 mAh g−1 at 1.0 A g−1 after 160 cycles. Even with the increased current density to 10.0 A g−1, the U‐TiO2/C electrode still performs a high capacity of 69.5 mAh g−1 after 2500 cycles. Detailed kinetic analysis has been investigated to quantificationally demonstrate that the surface pseudocapacitive storage behavior plays a dominant role in the enhanced sodium storage. [ABSTRACT FROM AUTHOR]

A novel nonparametric method based on manifold learning is proposed for industrial process monitoring. In conventional algorithms, to preserve the global and local structure information of data, heat kernels containing two auxiliary parameters are introduced to define the global and local weight matrices, respectively. However, it is difficult to identify and choose these two parameters empirically. The inadequate selection of parameters can lead to one‐sided and inappropriate global and local feature extractions, resulting in an inadequate fault detection performance. To resolve the above problems, a nonparametric strategy is used in this study to generate two nonparametric weight matrices to replace the heat kernel‐based weight matrices. Consequently, the proposed method requires no auxiliary parameters in defining the weight matrices, making it more practical. Moreover, it automatically determines a good trade‐off between global and local feature extractions. A process monitoring model based on the proposed method was developed. The feasibility and effectiveness of the new nonparametric method are evaluated using a synthetic example and the Tennessee Eastman chemical process. [ABSTRACT FROM AUTHOR]