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The discovery of brassinosteroids (BS) just over 20 years ago opened a new era in studies of bio-regulation in living organisms. Previously, the only known role of steroids as hormones was in animals and fungi; now a steroidal hormone in plants had been added. Progress in brassinosteroid research has been very rapid. Only 20 years passed between the discovery of brassinolide, the first member of the series, and the application of brassinosteroids in agriculture. Although the other plant hormones have been studied for a much longer period, there has not been similar development. Within the last couple of years two books on brassinosteroids (Khripach VA, Zhabinskii VN, de Groot A. 1999. Brassinosteroids—a new class of plant hormones. San Diego: Academic Press; Sakurai A, Yokota T, Clouse SD, eds. 1999. Brassinosteroids: steroidal plant hormones. Tokyo: Springer Verlag) have been published, but many new data have appeared since that time. Many of the more recent data is devoted to molecular biological aspects of BS and has helped to create a vision of their role in plants and their mechanisms of action. New discoveries of the physiological properties of BS allow us to consider them as highly promising, environmentally-friendly, natural substances suitable for wide application in plant protection and yield promotion in agriculture. This aspect of BS is the main subject of this Botanical Briefing.

Vitrimers are a new class of cross-linked materials that are capable of network topology alternation through the associative dynamic bond-exchange mechanism, which has recently been invented to solve the problem of conventional cross-linked materials, such as poor recyclability and healability. Thus far, the concept of vitrimers has been applied to various commercial polymers, e.g., polyesters, polylactides, polycarbonates, polydimethylsiloxanes, polydienes, polyurethanes, polyolefins, poly(meth)acrylates, and polystyrenes, by utilizing different compatible bond-exchange reactions. In this review article, the concept of vitrimers is described by clarifying the difference from thermoplastics and supramolecular systems; in addition, the term “associative bond-exchange” in vitrimers is explained by comparison with the “dissociative” term. Several useful functions attained by the vitrimer concept (including recyclability and healability) are demonstrated, and recent molecular designs of vitrimers are classified into groups depending on the types of molecular frameworks. This review specifically focuses on the vitrimer molecular designs with commercial polymer-based frameworks, which provide useful hints for the practical application of the vitrimer concept.

With the low redox potential of −3.04 V (vs SHE) and ultrahigh theoretical capacity of 3862 mAh g−1, lithium metal has been considered as promising anode material. However, lithium metal battery has ever suffered a trough in the past few decades due to its safety issues. Over the years, the limited energy density of the lithium‐ion battery cannot meet the growing demands of the advanced energy storage devices. Therefore, lithium metal anodes receive renewed attention, which have the potential to achieve high‐energy batteries. In this review, the history of the lithium anode is reviewed first. Then the failure mechanism of the lithium anode is analyzed, including dendrite, dead lithium, corrosion, and volume expansion of the lithium anode. Further, the strategies to alleviate the lithium anode issues in recent years are discussed emphatically. Eventually, remaining challenges of these strategies and possible research directions of lithium‐anode modification are presented to inspire innovation of lithium anode. The improvement of lithium anodes plays a great role in developing lithium metal batteries with high energy density. With the aim of enlighting the future directions of the researches on lithium anodes, the challenges and progress in the field of lithium anodes in recent years are presented.

HighlightsThe poly(1,3-dioxolane) (PDOL) electrolyte demonstrates promising potential for practical application due to its advantages in in-situ polymerization process, high ionic conductivity, and long cycle life.This review focuses on the polymerization mechanism, composite innovation, and application of PDOL electrolytes.This review provides a comprehensive summary of the challenges associated with the PDOL electrolyte and makes forward-looking recommendations.Polymer solid-state lithium batteries (SSLB) are regarded as a promising energy storage technology to meet growing demand due to their high energy density and safety. Ion conductivity, interface stability and battery assembly process are still the main challenges to hurdle the commercialization of SSLB. As the main component of SSLB, poly(1,3-dioxolane) (PDOL)-based solid polymer electrolytes polymerized in-situ are becoming a promising candidate solid electrolyte, for their high ion conductivity at room temperature, good battery electrochemical performances, and simple assembly process. This review analyzes opportunities and challenges of PDOL electrolytes toward practical application for polymer SSLB. The focuses include exploring the polymerization mechanism of DOL, the performance of PDOL composite electrolytes, and the application of PDOL. Furthermore, we provide a perspective on future research directions that need to be emphasized for commercialization of PDOL-based electrolytes in SSLB. The exploration of these schemes facilitates a comprehensive and profound understanding of PDOL-based polymer electrolyte and provides new research ideas to boost them toward practical application in solid-state batteries.

Plants play a crucial role in supplying food globally. Various environmental factors lead to plant diseases which results in significant production losses. However, manual detection of plant diseases is a time-consuming and error-prone process. It can be an unreliable method of identifying and preventing the spread of plant diseases. Adopting advanced technologies such as Machine Learning (ML) and Deep Learning (DL) can help to overcome these challenges by enabling early identification of plant diseases. In this paper, the recent advancements in the use of ML and DL techniques for the identification of plant diseases are explored. The research focuses on publications between 2015 and 2022, and the experiments discussed in this study demonstrate the effectiveness of using these techniques in improving the accuracy and efficiency of plant disease detection. This study also addresses the challenges and limitations associated with using ML and DL for plant disease identification, such as issues with data availability, imaging quality, and the differentiation between healthy and diseased plants. The research provides valuable insights for plant disease detection researchers, practitioners, and industry professionals by offering solutions to these challenges and limitations, providing a comprehensive understanding of the current state of research in this field, highlighting the benefits and limitations of these methods, and proposing potential solutions to overcome the challenges of their implementation.

The EQ-5D-Y-3L is a generic, health-related, quality-of-life instrument for use in younger populations. Some methodological studies have explored the valuation of children’s EQ-5D-Y-3L health states. There are currently no published value sets available for the EQ-5D-Y-3L that are appropriate for use in a cost-utility analysis. The aim of this article was to describe the development of the valuation protocol for the EQ-5D-Y-3L instrument. There were several research questions that needed to be answered to develop a valuation protocol for EQ-5D-Y-3L health states. Most important of these were: (1) Do we need to obtain separate values for the EQ-5D-Y-3L, or can we use the ones from the EQ-5D-3L? (2) Whose values should we elicit: children or adults? (3) Which valuation methods should be used to obtain values for child’s health states that are anchored in Full health = 1 and Dead = 0? The EuroQol Research Foundation has pursued a research programme to provide insight into these questions. In this article, we summarized the results of the research programme concluding with the description of the features of the EQ-5D-Y-3L valuation protocol. The tasks included in the protocol for valuing EQ-5D-Y-3L health states are discrete choice experiments for obtaining the relative importance of dimensions/levels and composite time-trade-off for anchoring the discrete choice experiment values on 1 = Full Health and 0 = Dead. This protocol is now available for use by research teams to generate EQ-5D-Y-3L value sets for their countries allowing the implementation of a cost-utility analysis for younger populations.

We provide a user guide on the analysis of data (including best–worst and best–best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a ‘way in’ for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

For several decades, the incremental cost-effectiveness ratio has been routinely used by health technology assessment agencies around the world to summarise the results of economic evaluations of health interventions. Yet reporting and considering incremental cost-effectiveness ratios is unnecessary. Alternative summary measures exist, based on the concept of ‘net benefit’. The incremental cost-effectiveness ratio and measures of net benefit share several commonalities but some important distinctions. As a result, different methods are required to calculate and interpret incremental cost-effectiveness ratios compared to measures of net benefit. The aim of this practical application is to introduce readers to these methods, using a hypothetical example to illustrate key issues. First, the methods used to calculate each measure are described. Next, for each measure, consideration is made of whether and how each measure may be interpreted to perform the following tasks, each of which may be of interest to health technology assessment agencies: (1) identifying the single most cost-effective strategy; (2) ranking strategies from ‘most’ to ‘least’ cost-effective (on an ordinal scale); (3) determining the magnitude to which a strategy is more or less cost-effective than another strategy (on a cardinal scale); and (4) determining whether a strategy is more or less cost-effective following a sensitivity or scenario analysis. This practical application also introduces a novel approach for visually interpreting measures of net benefit using the cost-effectiveness plane, which addresses a number of limitations of the conventional cost-effectiveness ‘efficiency frontier’. By the end of this practical application, readers should have an understanding of how to calculate and interpret each measure, as well as the relative strengths and limitations of each.

Single-atom catalysts 1 make exceptionally efficient use of expensive noble metals and can bring out unique properties 1 – 3 . However, applications are usually compromised by limited catalyst stability, which is due to sintering 3 , 4 . Although sintering can be suppressed by anchoring the metal atoms to oxide supports 1 , 5 , 6 , strong metal–oxygen interactions often leave too few metal sites available for reactant binding and catalysis 6 , 7 , and when exposed to reducing conditions at sufficiently high temperatures, even oxide-anchored single-atom catalysts eventually sinter 4 , 8 , 9 . Here we show that the beneficial effects of anchoring can be enhanced by confining the atomically dispersed metal atoms on oxide nanoclusters or ‘nanoglues’, which themselves are dispersed and immobilized on a robust, high-surface-area support. We demonstrate the strategy by grafting isolated and defective CeO x nanoglue islands onto high-surface-area SiO 2 ; the nanoglue islands then each host on average one Pt atom. We find that the Pt atoms remain dispersed under both oxidizing and reducing environments at high temperatures, and that the activated catalyst exhibits markedly increased activity for CO oxidation. We attribute the improved stability under reducing conditions to the support structure and the much stronger affinity of Pt atoms for CeO x than for SiO 2 , which ensures the Pt atoms can move but remain confined to their respective nanoglue islands. The strategy of using functional nanoglues to confine atomically dispersed metals and simultaneously enhance their reactivity is general, and we anticipate that it will take single-atom catalysts a step closer to practical applications. Nanometre-sized ‘nanoglue’ islands of CeO x on high-surface-area SiO 2 are shown to suppress sintering and confine on average one Pt atom per island, leading to stable single-atom catalysts under oxidizing and reducing environments.

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures. In this survey we aim to provide a more inclusive and high-level overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning. In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight the overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.