Summary
With the advent of rapid genotyping and next‐generation sequencing technologies, genome‐wide association study (GWAS) has become a routine strategy for decoding genotype–phenotype ...associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype–phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many ‘hits’ obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non‐main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome‐editing technologies.
Significance Statement
This review summarizes the latest advances in generating an overall view of the genetic architecture associated with crop complex traits, and discusses how these updated insights will guide future studies. A multiple‐causal‐allele hypothesis was formulated to explain the increasingly common artifact/synthetic associations.
Three‐dimensional (3D) printing, also known as additive manufacturing, is a fabrication method that has recently received worldwide attention. It provides a convenient and economical way to prepare ...3D structures in designable ways. As the technology has developed and the operational costs have decreased, the applications of 3D printing have greatly expanded. Catalyst fabrication is a promising area for 3D printing. Printing processes result in better control of catalyst structures and catalyst distribution. In this perspective, a general overview of the commonly available 3D printing methods that are feasible for the preparation of heterogeneous catalysts is given. Additionally, recent works on printing strategies and new materials for catalysts are discussed. Future development is also addressed.
Three‐dimensional (3D) printing is a fabrication method that has received worldwide attention. Recently, 3D printing has been applied to catalyst fabrication. In this perspective, a general overview of the commonly available 3D printing methods that are feasible for the preparation of heterogeneous catalysts is given. Recent works on printing strategies and new materials for catalysts are discussed. Future development is also addressed.
A look at how biochar is formed in the biomass pyrolysis process is offered. Research points toward a biochear-based sustainable platform carbon material.
This paper concentrates upon the problem of finite-time fault-tolerant control for a class of switched nonlinear systems in lower-triangular form under arbitrary switching signals. Both loss of ...effectiveness and bias fault in actuator are taken into account. The method developed extends the traditional finite-time convergence from nonswitched lower-triangular nonlinear systems to switched version by designing appropriate controller and adaptive laws. In contrast to the previous results, it is the first time to handle the fault tolerant problem for switched system while the finite-time stability is also necessary. Meanwhile, there exist unknown internal dynamics in the switched system, which are identified by the radial basis function neural networks. It is proved that under the presented control strategy, the system output tracks the reference signal in the sense of finite-time stability. Finally, an illustrative simulation on a resistor-capacitor-inductor circuit is proposed to further demonstrate the effectiveness of the theoretical result.
Plant diseases and pests are important factors determining the yield and quality of plants. Plant diseases and pests identification can be carried out by means of digital image processing. In recent ...years, deep learning has made breakthroughs in the field of digital image processing, far superior to traditional methods. How to use deep learning technology to study plant diseases and pests identification has become a research issue of great concern to researchers. This review provides a definition of plant diseases and pests detection problem, puts forward a comparison with traditional plant diseases and pests detection methods. According to the difference of network structure, this study outlines the research on plant diseases and pests detection based on deep learning in recent years from three aspects of classification network, detection network and segmentation network, and the advantages and disadvantages of each method are summarized. Common datasets are introduced, and the performance of existing studies is compared. On this basis, this study discusses possible challenges in practical applications of plant diseases and pests detection based on deep learning. In addition, possible solutions and research ideas are proposed for the challenges, and several suggestions are given. Finally, this study gives the analysis and prospect of the future trend of plant diseases and pests detection based on deep learning.
Developing environmentally friendly perovskites has become important in solving the toxicity issue of lead‐based perovskite solar cells. Here, the first double perovskite (Cs2AgBiBr6) solar cells ...using the planar structure are demonstrated. The prepared Cs2AgBiBr6 films are composed of high‐crystal‐quality grains with diameters equal to the film thickness, thus minimizing the grain boundary length and the carrier recombination. These high‐quality double perovskite films show long electron–hole diffusion lengths greater than 100 nm, enabling the fabrication of planar structure double perovskite solar cells. The resulting solar cells based on planar TiO2 exhibit an average power conversion efficiency over 1%. This work represents an important step forward toward the realization of environmentally friendly solar cells and also has important implications for the applications of double perovskites in other optoelectronic devices.
Cs2AgBiBr6 films composed of high‐crystal‐quality grains with diameters equal to the film thickness are fabricated. These high‐quality double‐perovskite films show electron–hole diffusion lengths greater than 100 nm, enabling the fabrication of planar‐structure double‐perovskite solar cells with a maximum value of 1.22%.
Recently, Ruddlesden–Popper perovskites (RPPs) have attracted increasing interests due to their promising stability. However, the efficiency of solar cells based on RPPs is much lower than that based ...on 3D perovskites, mainly attributed to their poor charge transport. Herein, a simple yet universal method for controlling the quality of RPP films by a synergistic effect of two additives in the precursor solution is presented. RPP films achieved by this method show (a) high quality with uniform morphology, enhanced crystallinity, and reduced density of sub‐bandgap states, (b) vertically oriented perovskite frameworks that facilitate efficient charge transport, and (c) type‐II band alignment that favors self‐driven charge separation. Consequently, a hysteresis‐free RPP solar cell with a power conversion efficiency exceeding 12%, which is much higher than that of the control device (1.5%), is achieved. The findings will spur new developments in the fabrication of high‐quality, aligned, and graded RPP films essential for realizing efficient and stable perovskite solar cells.
A simple and universal method involving the use of two synergistic additives (dimethylsulfoxide and methylammonium chloride) into precursor solution is reported for growing high‐quality Ruddlesden–Popper perovskite films. Based on this method, hysteresis‐free solar cells with power conversion efficiencies over 12% and excellent reproducibility are achieved.
In this paper, an adaptive fuzzy optimal control design is addressed for a class of unknown nonlinear discrete-time systems. The controlled systems are in a strict-feedback frame and contain unknown ...functions and nonsymmetric dead-zone. For this class of systems, the control objective is to design a controller, which not only guarantees the stability of the systems, but achieves the optimal control performance as well. This immediately brings about the difficulties in the controller design. To this end, the fuzzy logic systems are employed to approximate the unknown functions in the systems. Based on the utility functions and the critic designs, and by applying the backsteppping design technique, a reinforcement learning algorithm is used to develop an optimal control signal. The adaptation auxiliary signal for unknown dead-zone parameters is established to compensate for the effect of nonsymmetric dead-zone on the control performance, and the updating laws are obtained based on the gradient descent rule. The stability of the control systems can be proved based on the difference Lyapunov function method. The feasibility of the proposed control approach is further demonstrated via two simulation examples.
In this article, I explicitly solve dynamic portfolio choice problems, up to the solution of an ordinary differential equation (ODE), when the asset returns are quadratic and the agent has a constant ...relative risk aversion (CRRA) coefficient. My solution includes as special cases many existing explicit solutions of dynamic portfolio choice problems. I also present three applications that are not in the literature. Application 1 is the bond portfolio selection problem when bond returns are described by "quadratic term structure models." Application 2 is the stock portfolio selection problem when stock return volatility is stochastic as in Heston model. Application 3 is a bond and stock portfolio selection problem when the interest rate is stochastic and stock returns display stochastic volatility.
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