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The fixed time event‐triggered control for high‐order nonlinear uncertain systems with time‐varying full state constraints is investigated in this paper. First, the event‐triggered control (ETC) mechanism is introduced to reduce the data transmission in the communication channel. In consideration of the physical constraints and engineering requirements, time‐varying barrier Lyapunov function (BLF) is deployed to make all the system states confined in the given time‐varying constraints. Then, the radial basis function neural networks (RBF NNs) are used to approximate the unknown nonlinear terms. Further, the fixed time stability strategy is deployed to make the system achieve semiglobal practical fixed time stability (SPFTS) and the convergence time is independent of the initial conditions. Finally, the proposed control scheme is verified by two simulation examples. [ABSTRACT FROM AUTHOR]

Tin‐based perovskite solar cells (TPSCs) have received great attention due to their eco‐friendly properties and high theoretical efficiencies. However, the fast crystallization feature of tin‐based perovskites leads to poor film quality and limits the corresponding device performance. Herein, a chlorofullerene, C60Cl6, with six chlorine attached to the C60 cage, is applied to modulate the crystallization process and passivate grain boundary defects of the perovskite film. The chemical interactions between C60Cl6 and perovskite components retard the transforming process of precursors to perovskite crystals and obtain a high‐quality tin‐based perovskite film. It is also revealed that the C60Cl6 located at the surfaces and grain boundaries can not only passivate the defects but also offer a role in suturing grain boundaries to suppress the detrimental effects of water and oxygen on perovskite films, especially the oxidation of Sn2+ to Sn4+. As a result, the C60Cl6‐based device yields a remarkably improved device efficiency from 10.03% to 13.30% with enhanced stability. This work provides a new strategy to regulate the film quality and stability of TPSCs using functional fullerene materials. [ABSTRACT FROM AUTHOR]

Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. The HLM approach is flexible and can model a variety of different SCED data complexities, such as intervention heterogeneity. A major advantage of using HLM is that participant and-or study characteristics can be incorporated in the model in an attempt to explain intervention heterogeneity. The inclusion of moderators in the context of meta-analysis of SCED studies did not yet receive attention and is in need of methodological research. Prior to extending methodological work validating the hierarchical linear model including moderators at the different levels, an overview of characteristics of moderators typically encountered in the field is needed. This will inform design conditions to be embedded in future methodological studies and ensure that these conditions are realistic and representative for the field of SCED meta-analyses. This study presents the results of systematic review of SCED meta-analyses, with the particular focus on moderator characteristic. The initial search yielded a total of 910 articles and book chapters. After excluding duplicate studies and non peer-reviewed studies, 658 unique peer-reviewed studies were maintained and screened by two independent researchers. Sixty articles met the inclusion criteria and were eligible for data retrieval. The results of the analysis of moderator characteristics retrieved from these 60 meta-analyses are presented. The first part of the results section contains an overview of moderator characteristics per moderator level (within-participant level, participant level, and study level), including the types of moderators, the ratio of the number of moderators relative to the number of units at that level, the measurement scale, and the degree of missing data. The second part of the results section focuses on the metric used to quantify moderator effectiveness and the analysis approach. Based on the results of the systematic review, recommendations are given for conditions to be included in future methodological work. [ABSTRACT FROM AUTHOR]

The adjoint of the GEOS-Chem (Goddard Earth Observing System with Chemistry) model has been widely used to constrain the sources of atmospheric compositions. Here, we designed a new framework to facilitate emission inventory updates in the adjoint of the GEOS-Chem model. The major advantage of this new framework is good readability and extensibility, which allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) meteorological data, which allows us to perform long-term analyses with consistent meteorological data for the period 1979–present. The performances of the developed capabilities were evaluated with the following steps: (1) diagnostic outputs of carbon monoxide (CO) sources and sinks to ensure the correct reading and use of emission inventories, (2) forward simulations to compare the modeled surface and column CO concentrations among various model versions, (3) backward simulations to compare adjoint gradients of global CO concentrations to CO emissions with finite-difference gradients, and (4) observing system simulation experiments (OSSEs) to evaluate the model performance in 4D variational (4D-Var) assimilations. Finally, an example application of 4D-Var assimilation was presented to constrain anthropogenic CO emissions in 2015 by assimilating Measurement of Pollution in the Troposphere (MOPITT) CO observations. The capabilities developed in this work are important for better applications of the adjoint of the GEOS-Chem model in the future. These capabilities will be submitted to the standard GEOS-Chem adjoint code base for better development of the community of the adjoint of the GEOS-Chem model. [ABSTRACT FROM AUTHOR]