Fluorinated ketones are widely prevalent in numerous biologically interesting molecules, and the development of novel transformations to access these structures is an important task in organic ...synthesis. Herein, we report the multicomponent radical acylfluoroalkylation of a variety of olefins in the presence of various commercially available aromatic aldehydes and fluoroalkyl reagents through N‐heterocyclic carbene organocatalysis. With this protocol, over 120 examples of functionalized ketones with diverse fluorine substituents have been synthesized in up to 99 % yield with complete regioselectivity. The generality of this catalytic strategy was further highlighted by its successful application in the late‐stage functionalization of pharmaceutical skeletons. Excellent diastereoselectivity could be achieved in the reactions forging multiple stereocenters. In addition, preliminary results have been achieved on the catalytic asymmetric variant of the olefin difunctionalization process.
Organocatalytic acylfluoroalkylation: A multicomponent radical acylfluoroalkylation of olefins through NHC organocatalysis was developed, and over 120 examples of fluoroketones were facilely accessed from simple materials. Moreover, a dearomative difunctionalization of indoles could be readily achieved in a highly diastereoselective manner. The generality and practicality were highlighted by the late‐stage modification of drug skeletons.
Conversion of levulinic acid to valuable chemicals: a review Xu, Wen‐Ping; Chen, Xue‐Fang; Guo, Hai‐Jun ...
Journal of chemical technology and biotechnology (1986),
November 2021, 2021-11-00, 20211101, Letnik:
96, Številka:
11
Journal Article
Although previous studies have found that melatonin can promote seed germination, the mechanisms involved in perceiving and signaling melatonin remain poorly understood. In this study, it was found ...that melatonin was synthesized during cucumber seed germination with a peak in melatonin levels occurring 14 hr into germination. This is indicative of a correlation between melatonin synthesis and seed germination. Meanwhile, seeds pretreated with exogenous melatonin (1 μm) showed enhanced germination rates under 150 mm NaCl stress compared to water‐pretreated seeds under salinity stress. There are two apparent mechanisms by which melatonin alleviated salinity‐induced inhibition of seed germination. Exogenous melatonin decreased oxidative damage induced by NaCl stress by enhancing gene expression of antioxidants. Under NaCl stress, compared to untreated control, the activities of antioxidant enzymes including superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) were significantly increased by approximately 1.3–5.0‐fold, with a concomitant 1.4–2.0‐fold increase of CsCu‐ZnSOD, CsFe‐ZnSOD, CsCAT, and CsPOD in melatonin‐pretreated seeds. Melatonin also alleviated salinity stress by affecting abscisic acid (ABA) and gibberellin acid (GA) biosynthesis and catabolism during seed germination. Compared to NaCl treatment, melatonin significantly up‐regulated ABA catabolism genes (e.g., CsCYP707A1 and CsCYP707A2, 3.5 and 105‐fold higher than NaCl treatment at 16 hr, respectively) and down‐regulated ABA biosynthesis genes (e.g., CsNECD2, 0.29‐fold of CK2 at 16 hr), resulting in a rapid decrease of ABA content during the early stage of germination. At the same time, melatonin positively up‐regulated GA biosynthesis genes (e.g., GA20ox and GA3ox, 2.3 and 3.9‐fold higher than NaCl treatment at 0 and 12 hr, respectively), contributing to a significant increase of GA (especially GA4) content. In this study, we provide new evidence suggesting that melatonin alleviates the inhibitory effects of NaCl stress on germination mainly by regulating the biosynthesis and catabolism of ABA and GA4.
Optimality of the premise, IF part is critical to a zero-order evolving intelligent system (EIS) because this part determines the validity of the learning results and overall system performance. ...Nonetheless, a systematic analysis of optimality has not been done yet in the state-of-the-art works. In this paper, we use the recently introduced self-organising neuro-fuzzy inference system (SONFIS) as an example of typical zero-order EISs and analyse the local optimality of its solutions. The optimality problem is firstly formulated in a mathematical form, and detailed optimality analysis is conducted. The conclusion is that SONFIS does not generate a locally optimal solution in its original form. Then, an optimisation method is proposed for SONFIS, which helps the system to attain local optimality in a few iterations using historical data. Numerical examples presented in this paper demonstrate the validity of the optimality analysis and the effectiveness of the proposed optimisation method. In addition, it is further verified numerically that the proposed concept and general principles can be applied to other types of zero-order EISs with similar operating mechanisms.
The brown planthopper, Nilaparvata lugens, the most destructive pest of rice, is a typical monophagous herbivore that feeds exclusively on rice sap, which migrates over long distances. Outbreaks of ...it have re-occurred approximately every three years in Asia. It has also been used as a model system for ecological studies and for developing effective pest management. To better understand how a monophagous sap-sucking arthropod herbivore has adapted to its exclusive host selection and to provide insights to improve pest control, we analyzed the genomes of the brown planthopper and its two endosymbionts.
We describe the 1.14 gigabase planthopper draft genome and the genomes of two microbial endosymbionts that permit the planthopper to forage exclusively on rice fields. Only 40.8% of the 27,571 identified Nilaparvata protein coding genes have detectable shared homology with the proteomes of the other 14 arthropods included in this study, reflecting large-scale gene losses including in evolutionarily conserved gene families and biochemical pathways. These unique genomic features are functionally associated with the animal's exclusive plant host selection. Genes missing from the insect in conserved biochemical pathways that are essential for its survival on the nutritionally imbalanced sap diet are present in the genomes of its microbial endosymbionts, which have evolved to complement the mutualistic nutritional needs of the host.
Our study reveals a series of complex adaptations of the brown planthopper involving a variety of biological processes, that result in its highly destructive impact on the exclusive host rice. All these findings highlight potential directions for effective pest control of the planthopper.
Correntropy-Based Evolving Fuzzy Neural System Bao, Rong-Jing; Rong, Hai-Jun; Angelov, Plamen P. ...
IEEE transactions on fuzzy systems,
2018-June, 2018-6-00, Letnik:
26, Številka:
3
Journal Article
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In this paper, a correntropy-based evolving fuzzy neural system (CEFNS) is proposed for approximation of nonlinear systems. Different from the commonly used mean-square error criterion, correntropy ...has a strong outliers rejection ability through capturing the higher moments of the error distribution. Considering the merits of correntropy, this paper brings contributions to build evolving fuzzy neural system (EFNS) based on the correntropy concept to achieve a more stable evolution of the rule base and update of the rule parameters instead of the commonly used mean-square error criterion. The correntropy-EFNS (CEFNS) begins with an empty rule base, and all rules are evolved online based on the correntropy criterion. The consequent part parameters are tuned based on the maximum correntropy criterion, where the correntropy is used as the cost function so as to improve the non-Gaussian noise rejection ability. The steady-state convergence performance of the CEFNS is studied through the calculation of the steady-state excess mean square error (EMSE) in two cases: Gaussian noise; and non-Gaussian noise. Finally, the CEFNS is validated through a benchmark system identification problem, a Mackey-Glass time series prediction problem as well as five other real-world benchmark regression problems under both noise-free and noisy conditions. Compared with other EFNSs, the simulation results show that the proposed CEFNS produces better approximation accuracy using the least number of rules and training time and also owns superior non-Gaussian noise handling capability.
The brown planthopper (BPH) Nilaparvata lugens (Stål) is one of the most serious insect pests of rice in Asia. However, little is known about the mechanisms responsible for the development, wing ...dimorphism and sex difference in this species. Genomic information for BPH is currently unavailable, and, therefore, transcriptome and expression profiling data for this species are needed as an important resource to better understand the biological mechanisms of BPH.
In this study, we performed de novo transcriptome assembly and gene expression analysis using short-read sequencing technology (Illumina) combined with a tag-based digital gene expression (DGE) system. The transcriptome analysis assembles the gene information for different developmental stages, sexes and wing forms of BPH. In addition, we constructed six DGE libraries: eggs, second instar nymphs, fifth instar nymphs, brachypterous female adults, macropterous female adults and macropterous male adults. Illumina sequencing revealed 85,526 unigenes, including 13,102 clusters and 72,424 singletons. Transcriptome sequences larger than 350 bp were subjected to Gene Orthology (GO) and KEGG Orthology (KO) annotations. To analyze the DGE profiling, we mainly compared the gene expression variations between eggs and second instar nymphs; second and fifth instar nymphs; fifth instar nymphs and three types of adults; brachypterous and macropterous female adults as well as macropterous female and male adults. Thousands of genes showed significantly different expression levels based on the various comparisons. And we randomly selected some genes to confirm their altered expression levels by quantitative real-time PCR (qRT-PCR).
The obtained BPH transcriptome and DGE profiling data provide comprehensive gene expression information at the transcriptional level that could facilitate our understanding of the molecular mechanisms from various physiological aspects including development, wing dimorphism and sex difference in BPH.
Evolving fuzzy systems (EFSs) are now well developed and widely used, thanks to their ability to self-adapt both their structures and parameters online. Since the concept was first introduced two ...decades ago, many different types of EFSs have been successfully implemented. However, there are only very few works considering the stability of the EFSs, and these studies were limited to certain types of membership functions with specifically predefined parameters, which largely increases the complexity of the learning process. At the same time, stability analysis is of paramount importance for control applications and provides the theoretical guarantees for the convergence of the learning algorithms. In this paper, we introduce the stability proof of a class of EFSs based on data clouds, which are grounded at the AnYa type fuzzy systems and the recently introduced empirical data analytics (EDA) methodological framework. By employing data clouds, the class of EFSs of AnYa type considered in this paper avoids the traditional way of defining membership functions for each input variable in an explicit manner and its learning process is entirely data driven. The stability of the considered EFS of AnYa type is proven through the Lyapunov theory, and the proof of stability shows that the average identification error converges to a small neighborhood of zero. Although, the stability proof presented in this paper is specially elaborated for the considered EFS, it is also applicable to general EFSs. The proposed method is illustrated with Box-Jenkins gas furnace problem, one nonlinear system identification problem, Mackey-Glass time series prediction problem, eight real-world benchmark regression problems as well as a high-frequency trading prediction problem. Compared with other EFSs, the numerical examples show that the considered EFS in this paper provides guaranteed stability as well as a better approximation accuracy.
In this article, a novel recursive maximum correntropy-based evolving fuzzy system (RMCEFS) is proposed. The proposed system has the capability of reorganizing the structure and adapting itself in a ...dynamically changing environment with non-Gaussian noises. The system generates a new rule based on the correntropy criterion which represents a robust nonlinear similarity measure between two random variables and avoids recruiting the noises as the rules. Maximizing the cross-correntropy between the system output and the desired response leads to the maximum correntropy criterion for system self-adaptation. In our article, a recursive solution of the maximum correntropy criterion is derived to update the parameters of the evolving rules. This avoids the convergence problem produced by the learning size in the gradient-based learning. Also, the steady-state convergence performance of the proposed RMCEFS is studied, where the analytical solutions of the steady-state excess mean square error for the Gaussian noise and non-Gaussian noises are derived. The simulation studies show that the proposed RMCEFS using the recursive maximum correntropy converges much faster and is more accurate than the existing evolving fuzzy systems in the case of noise-free and noisy conditions.
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