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Amaranthus tricolor is a vegetable and ornamental amaranth, with high lysine, dietary fibre and squalene content. The red cultivar of A. tricolor possesses a high concentration of betalains, which has been used as natural food colorants. Here, we constructed the genome of A. tricolor , the first reference genome for the subgenus Albersia , combining PacBio HiFi, Nanopore ultra-long and Hi–C data. The contig N50 size was 906 kb, and 99.58% of contig sequence was anchored to the 17 chromosomes, totalling 520 Mb. We annotated 27,813 protein-coding genes with an average 1.3 kb coding sequence and 5.3 exons. We inferred that A. tricolor underwent a whole-genome duplication (WGD) and that the WGD shared by amaranths occurred in the last common ancestor of subfamily Amaranthoideae. Moreover, we comprehensively identified candidate genes in betalain biosynthesis pathway. Among them, DODAα1 and CYP76ADα1 , located in one topologically associated domain (TAD) of an active (A) compartment on chromosome 16, were more highly expressed in red leaves than in green leaves, and DODAα1 might be the rate-limiting enzyme gene in betalains biosynthesis. This study presents new genome resources and enriches our understanding of amaranth evolution, betalains production, facilitating molecular breeding improvements and the understanding of C4 plants evolution. [ABSTRACT FROM AUTHOR]

Background Due to the importance of chicken production and the remarkable influence of the gut microbiota on host health and growth, tens of thousands of metagenome-assembled genomes (MAGs) have been constructed for the chicken gut microbiome. However, due to the limitations of short-read sequencing and assembly technologies, most of these MAGs are far from complete, are of lower quality, and include contaminant reads. Results We generated 332 Gb of high-fidelity (HiFi) long reads from the 5 chicken intestinal compartments and assembled 461 and 337 microbial genomes, of which 53% and 55% are circular, at the species and strain levels, respectively. For the assembled microbial genomes, approximately 95% were regarded as complete according to the "RNA complete" criteria, which requires at least 1 full-length ribosomal RNA (rRNA) operon encoding all 3 types of rRNA (16S, 23S, and 5S) and at least 18 copies of full-length transfer RNA genes. In comparison with the short-read-derived chicken MAGs, 384 (83% of 461) and 89 (26% of 337) strain-level and species-level genomes in this study are novel, with no matches to previously reported sequences. At the gene level, one-third of the 2.5 million genes in the HiFi-derived gene catalog are novel and cannot be matched to the short-read-derived gene catalog. Moreover, the HiFi-derived genomes have much higher continuity and completeness, as well as lower contamination; the HiFi-derived gene catalog has a much higher ratio of complete gene structures. The dominant phylum in our HiFi-assembled genomes was Firmicutes (82.5%), and the foregut was highly enriched in 5 genera: Ligilactobacillus, Limosilactobacillus, Lactobacillus, Weissella , and Enterococcus , all of which belong to the order Lactobacillales. Using GTDB-Tk, all 337 species-level genomes were successfully classified at the order level; however, 2, 35, and 189 genomes could not be classified into any known family, genus, and species, respectively. Among these incompletely classified genomes, 9 and 49 may belong to novel genera and species, respectively, because their 16S rRNA genes have identities lower than 95% and 97% to any known 16S rRNA genes. Conclusions HiFi sequencing not only produced metagenome assemblies and gene structures with markedly improved quality but also recovered a substantial portion of novel genomes and genes that were missed in previous short-read-based metagenome studies. The novel genomes and species obtained in this study will facilitate gut microbiome and host–microbiota interaction studies, thereby contributing to the sustainable development of poultry resources. [ABSTRACT FROM AUTHOR]

Background The globe skimmer dragonfly (Pantala flavescens) is a notable Odonata insect distributed in nature fields and farmlands worldwide, and it is commonly recognized as a natural enemy because it preys on agricultural pests and health pests. As one of the sister groups of winged insects, odonatan species are key to understanding the evolution of insect wings. Findings We present a high-quality reference genome of P. flavescens , which is the first chromosome-level genome in the Palaeoptera (Odonata and Ephemeroptera). The assembled genome size was 662 Mb, with a contig N50 of 16.2 Mb. Via Hi-C scaffolding, 648 Mb (97.9%) of contig sequences were clustered, ordered, and assembled into 12 large scaffolds, each corresponding to a natural chromosome. The X chromosome was identified by sequence coverage depth. The repetitive sequences and gene density of the X chromosome are similar to those of autosomal sequences, but the X chromosome shows a much lower degree of heterozygosity. Our analysis shows that the effective population size experienced 3 declining events, which may have been caused by climate change and environmental pollution. Conclusions The genome of P. flavescens provides more information on the biology and evolution of insects and will help for the use of this species in pest control. [ABSTRACT FROM AUTHOR]

This article uses acoustic emission (AE) analysis to diagnose an industrial-scale and slow-speed wind turbine blade bearing. The main challenge for AE analysis is that the fault signals are mingled with heavy noise. As a result, the objective of this article is to filter the raw AE signals and extract weak fault signals. To achieve this goal, a general linear and nonlinear auto-regressive (GLNAR) model is first developed to exploit the nonlinear characteristics of the AE signals. Then, the sparse augmented Lagrangian (SAL) algorithm is applied to learn the built GLNAR model and filter the raw AE signals. The characteristics of SAL is that it is a novel sparse representation technique which can convert the original filtering problem into a number of suboptimization problems, and these subproblems can be solved separately. Finally, as the blade bearing rotates at fluctuating speeds, the filtered signals are resampled so that the bearing fault type can be diagnosed in the order domain. The proposed diagnostic framework was validated in several experiments under time-varying low-speed and heavy-blade-load conditions. The results indicate that our proposed methods are effective and accurate. [ABSTRACT FROM AUTHOR]

Fault diagnosis under time-varying operational conditions is always the challenge in industrial systems. The chirplet transform (CT) provides an effective first-order approximation approach, but the slow operation speed and the drawback for high-order signal analysis limit its uses. Focusing on this problem, a fast nonlinear chirplet dictionary-based sparse decomposition (FNC-SD) method for nonlinear signal analysis is proposed. By replacing the time–frequency inclination parameter in the CT with a frequency bending parameter, the proposed method can track the nonstationary signals by arbitrary order polynomial law with time by an additional degree. Considering that too many parameters will slow down the operation speed, a frequency bending operator estimation algorithm is also proposed in this paper based on the calculated rotating frequency. Therefore, a laser vibrometer is needed in the experiment to collect the impulse signals, which can represent rotating speed signals. Then, the FNC-SD method is used to construct a redundant dictionary for signal sparse time–frequency representation. The high similarity between signals and atoms can make the method prefer to choose the right atoms, instead of being influenced by noise. Therefore, the proposed method also shows a strong noise robustness. Two simulation experiments are constructed to verify the performance of the proposed method. Finally, the FNC-SD method is used to diagnose a faulty motor with broken bar. The analyzed results and comparisons with respect to the state-of-the-art methods are illustrated in detail, as well as the convergence accuracy and speed, which highlight the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Remaining useful life (RUL) prediction has been increasingly considered in many industrial fields for the reliability and safety of their systems. As a data analysis tool of deep learning, deep convolutional neural network (CNN) shows great potential for RUL prediction. This paper proposes an intelligent RUL prediction method based on a double-CNN model architecture. Given the powerful feature extraction capability of CNN, the proposed method is fed with original vibration signals with no need to resort to any feature extractor, which can also retain the useful information in maximum. The prediction includes two stages: first, incipient fault point is identified by the first CNN model and a proposed “3/5” principle; then, the second CNN model is constructed for RUL prediction. In practice, RULs of identical components are different from each other, which poses a major challenge in RUL prediction. To overcome this problem, an intermediate reliability variable is first calculated in this paper, instead of directly predicting the RUL value. Then, a mapping algorithm is proposed to map reliability to RUL. To demonstrate the effectiveness of the proposed method, data of four tests of bearing degradation are utilized for RUL prediction. Compared with state-of-the-art methods, the proposed method shows higher prediction accuracy and robustness. The prediction results and evaluation indexes demonstrated the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

As wind power attracts increasing attention and wind turbines (WTs) capacity expands, fault diagnosis of WT is playing a more and more important role in improving reliability, minimizing down time, reducing maintenance costs, and providing reliable power generation. In this paper, a novel sparse time-frequency representation (STFR) method is proposed to increase the diagnostic precision of incipient faults. The proposed method can be applied once the condition is detected as abnormal according to the VDI3834 vibration threshold standard in WT fault diagnosis systems. The proposed method is a novel signal representation method based on the sparse representation theory and Wigner–Ville distribution (WVD), which can overcome the limitations of traditional basis functions expansion and time-frequency analysis methods. In this method, a union of redundant dictionary (URD) is constructed on the basis of the underlying prior information of the oscillate characteristics with multicomponent coupling effect and different morphological waveforms. Therefore, the vibration signal can be sparsely represented over the URD. Then, the sparse coefficients and corresponding atoms can be obtained by solving the basis pursuit denoising problem via alternating direction method of multipliers. Based on the combination of the WVD of each atom and corresponding sparse coefficient, the time-frequency distribution of the vibration signal can be obtained. To verify the effectiveness of the STFR method, a simulation and two field tests in the wind farm are performed. The comparison results with state-of-the-art methods illustrate the superiority and robustness of the proposed method in the engineering applications. [ABSTRACT FROM AUTHOR]

Machine fault diagnosis collects massive amounts of vibration data about complex mechanical systems. Performing feature detection from these data sets has already led to a major challenge. Compressive sensing theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory. This theory enables the recovery of sparse or compressible signals from a small set of nonadaptive linear measurements. However, it is suboptimal to recover the whole signals from the compressive measurements and then solve feature identification problems through traditional DSP techniques. Thus, a novel mechanical feature identification method is proposed in this paper. Its main advantage is that fault features are extracted directly in the compressive measurement domain without sacrificing accuracy, while a significant reduction in the dimensionality of the measurement data is achieved. Moreover, Gaussian white noises are significantly alleviated, which dramatically enhances the reliability of machine fault diagnosis. Parameter analysis is also profoundly investigated through a set of numerical experiments. Numerical simulations and experiments are further performed to prove the reliability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Agricultural intensification has increased crop productivity but simplified production and reduced cropping system diversity. In recent decades, the intensified wheat–maize rotation in the North China Plain has sharply decreased the groundwater table, with associated environmental and biodiversity issues. Understanding whether increasing cropping system diversity stabilizes productivity, improves resilience, and reduces adverse environmental impacts is critical. This study quantified the water requirements of nine staple crops from 1960 to 2020, established 15 alternative crop rotations, and evaluated the resilience of each rotation in the Cangzhou area, a typical groundwater deletion funnel area. The results showed that reducing cropping density (harvests per year) from 2 to 1.5 decreased the average annual water requirement and irrigation demand by 14 % and 33 %, respectively. Summer soybean alternated with maize and rotated with wheat did not reduce groundwater use but increased profitability and protein production. Spring mung bean–summer millet-based multi-rotations had higher precipitation coupling degrees (8 % in wet years, 17 % in normal years, and 56 % in dry years) and profitability (1.1–2.4 times) than the wheat–maize rotation. The spring potato–summer millet rotation in one year had the greatest profitability, the highest equivalent yield to wheat, and the highest water use efficiency (WUE), while spring maize rotated with winter wheat–summer soybean performed best for protein content, energy output, and WUEs. This study identified 11 alternative rotations with a higher comprehensive evaluation index than the conventional wheat–maize rotation based on entropy-TOPSIS considering 12 indicators. Spring mungbean is not suitable for inclusion in the crop rotation when solely cultivated in one year due to mismatched rainfall. Beyond wheat and maize, soybean, millet, and potato are promising crops for innovative multi-year multi-crop rotations to enhance crop diversification, maximize system outputs, and minimize groundwater and energy depletion. This study's analysis could be extended to develop robust and diverse crop rotations with multiple co-benefits in other water-stressed agricultural regions. • Water requirements of nine staple crops from 1960 to 2020 was quantified. • 15 diversified crop rotations were redesigned and established. • Multi-dimensional outcomes of each rotation were evaluated for synergies and tradeoff. • Reducing cropping density mitigated groundwater table decline. • Wheat-maize rotations involving soybean, millet and potato achieved multiple co-benefits. [ABSTRACT FROM AUTHOR]

Chinese herbal medicines (CHMs), with a wide range of bioactive components, are considered to be an important source for new drug discovery. However, the process to isolate and obtain those bioactive components to develop new drugs always consumes a large amount of organic solvents with high toxicity and non-biodegradability. Natural deep eutectic solvents (NADES), a new type of green and designable solvents composed of primary plant-based metabolites, have been used as eco-friendly substitutes for traditional organic solvents in various fields. Due to the advantages of easy preparation, low production cost, low toxicity, and eco-friendliness, NADES have been also applied as extraction solvents, media, and drug delivery agents in CHMs in recent years. Besides, the special properties of NADES have been contributed to elucidating the traditional processing (also named Paozhi in Chinese) theory of CHMs, especially processing with honey. In this paper, the development process, preparation, classification, and applications for NADES in CHMs have been reviewed. Prospects in the future applications and challenges have been discussed to better understand the possibilities of the new solvents in the drug development and other uses of CHMs., Competing Interests: Author MW was employed by the company SU Biomedicine BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Rao, Ye, Wang, Yang, Wang, Guo, Xiong and Cui.)

Background: Anaerobic digestion (AD) is important in treating of food waste, and thousands of metagenome-assembled genomes (MAGs) have been constructed for the microbiome in AD. However, due to the limitations of the short-read sequencing and assembly technologies, most of these MAGs are grouped from hundreds of short contigs by binning algorithms, and the errors are easily introduced., Results: In this study, we constructed a total of 60 non-redundant microbial genomes from 64.5 Gb of PacBio high-fidelity (HiFi) long reads, generated from the digestate samples of a full-scale biogas plant fed with food waste. Of the 60 microbial genomes, all genomes have at least one copy of rRNA operons (16S, 23S, and 5S rRNA), 54 have ≥18 types of standard tRNA genes, and 39 are circular complete genomes. In comparison with the published short-read derived MAGs for AD, we found 23 genomes with average nucleotide identity less than 95% to any known MAGs. Besides, our HiFi-derived genomes have much higher average contig N50 size, slightly higher average genome size and lower contamination. GTDB-Tk classification of these genomes revealed two genomes belonging to novel genus and four genomes belonging to novel species, since their 16S rRNA genes have identities lower than 95 and 97% to any known 16S rRNA genes, respectively. Microbial community analysis based on the these assembled genomes reveals the most predominant phylum was Thermotogae (70.5%), followed by Euryarchaeota (6.1%), and Bacteroidetes (4.7%), and the most predominant bacterial and archaeal genera were Defluviitoga (69.1%) and Methanothrix (5.4%), respectively. Analysis of the full-length 16S rRNA genes identified from the HiFi reads gave similar microbial compositions to that derived from the 60 assembled genomes., Conclusion: High-fidelity sequencing not only generated microbial genomes with obviously improved quality but also recovered a substantial portion of novel genomes missed in previous short-read based studies, and the novel genomes will deepen our understanding of the microbial composition in AD of food waste., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Jiang, Li, Wang, Shen, Wang, Wang, Xu, Yuan, Lei, Chen, Yang, Deng and Fan.)

Ipomoea cairica is a perennial creeper that has been widely introduced as a garden ornamental across tropical, subtropical, and temperate regions. Because it grows extremely fast and spreads easily, it has been listed as an invasive species in many countries. Here, we constructed the chromosome-level reference genome of Ipomoea cairica by Pacific Biosciences HiFi and Hi-C sequencing, with the assembly size of 733.0 Mb, the contig N50 of 43.8 Mb, the scaffold N50 of 45.7 Mb, and the Benchmarking Universal Single-Copy Orthologs complete rate of 98.0%. Hi-C scaffolding assigned 97.9% of the contigs to 15 pseudo-chromosomes. Telomeric repeat analysis reveals that 7 of the 15 pseudo-chromosomes are gapless and telomere to telomere. The transposable element content of Ipomoea cairica is 73.4%, obviously higher than that of other Ipomoea species. A total of 38,115 protein-coding genes were predicted, with the Benchmarking Universal Single-Copy Orthologs complete rate of 98.5%, comparable to that of the genome assembly, and 92.6% of genes were functional annotated. In addition, we identified 3,039 tRNA genes and 2,403 rRNA genes in the assembled genome. Phylogenetic analysis showed that Ipomoea cairica formed a clade with Ipomoea aquatica, and they diverged from each other 8.1 million years ago. Through comparative genome analysis, we reconfirmed that a whole genome triplication event occurred specific to Convolvulaceae family and in the ancestor of the genus Ipomoea and Cuscuta. This high-quality reference genome of Ipomoea cairica will greatly facilitate the studies on the molecular mechanisms of its rapid growth and invasiveness., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)

Lead (Pb) in lipstick products has become an increasing concern, which can cause safety problems to human body directly with diet. To investigate the Pb exposure and potential health risk level of typical popular lip cosmetics in Chinese e-commerce market, Python crawler was introduced to identify and select 34 typical popular lip cosmetics, including 12 lipsticks, 13 lip glosses, and 9 lip balms. And then this study used ICP-MS to determine the content of Pb. Furthermore, the ingestion health risk assessment method issued by United States Environmental Protection Agency (USEPA) and Monte Carlo simulation algorithm were applied to assess the probabilistic health risks of adults exposure. Finally, taking the possible exposure of children contacting with lip products, the health risk assessment of children blood Pb was carried out. The results showed that the concentration of Pb in lip products ranged from 0 to 0.5237 mg/kg, which was far lower than the limit set by various countries. The probabilistic non-carcinogenic risks and carcinogenic risks were 4.93 ×10 -7 ~2.82 ×10 -3 and 1.68 ×10 -12 ~9.59 ×10 -9 , respectively, which were in an acceptable level. The results of blood Pb assessment suggested that the Pb content of lip cosmetics had no obvious influence on blood Pb concentration of children, and background Pb exposure is the main factor affecting children's blood Pb level (BLL). Overall, the samples of lip products are selected by Python crawler in this study, which are more objective and representative. This study focuses on deeper study of Pb, especially for the health risk assessment of blood Pb in children exposed to lip products. These results perhaps could provide useful information for the safety cosmetics usage for people in China and even the global world., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Li, Fang, Liu, Zhang, Liu, Jiang, Yang, Yang, Song and Liu.)

The regular hexagonal array morphology of facets (ommatidia) in the Drosophila compound eye is accomplished by regulation of cell differentiation and planar cell polarity during development. Mutations in certain genes disrupt regulation, causing a breakdown of this perfect symmetry, so that the ommatidial pattern shows onset of disorder in the form of packing defects. We analyze a variety of such mutants and compare them to normal (wild-type), finding that mutants show increased local variation in ommatidial area, which is sufficient to induce a significant number of defects. A model formalism based on Voronoi construction is developed to predict the observed correlation between ommatidium size variation and the number of defects, and to study the onset of disorder in this system with statistical tools. The model uncovers a previously unknown large-scale systematic size variation of the ommatidia across the eye of both wild-type and mutant animals. Such systematic variation of area, as well as its statistical fluctuations, are found to have distinct effects on eye disorder that can both be quantitatively modeled. Furthermore, the topological order is also influenced by the internal structure of the ommatidia, with cells of greater relative mechanical stiffness providing constraints to ommatidial deformation and thus to defect generation. Without free parameters, the simulation predicts the size-topology correlation for both wild-type and mutant eyes. This work develops formalisms of size-topology correlation that are very general and can be potentially applied to other cellular structures near the onset of disorder., (Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

We incorporated ultrafine polymer fibers into calcium phosphate cement (CPC) to improve the resorption rate of CPC with fiber degradation. Different weight percentages of electrospun poly(ε-caprolactone) fibers (0%, 3%, and 7%, named as ultrafine fiber-incorporated CPC0 [UFICPC0], UFICPC3, and UFICPC7) were included into preset CPC specimens for in vitro immersion in lipase phosphate-buffered solution and long-term in vivo implantation in the femoral condyle of rabbits. The effect of the ultrafine poly(ε-caprolactone) fibers with a diameter ranging from nanometer to micrometer on CPC degradation was evaluated by measuring the pH of the medium, mass loss, porosity, and physiochemical properties. For the in vivo evaluation, histomorphometrical analysis as well as three-dimensional (3D) reconstruction was applied to assess the osteogenic properties of the CPC composite. After in vitro immersion and in vivo implantation, the total porosity and macroporosity as well as the bone formation and ingrowth increased significantly during time in the fiber-incorporated CPC specimens. After 24 weeks of implantation, the degraded space was occupied by newly formed bone, and the UFICPC3 and UFICPC7 composites showed ~3.5 times higher fraction of bone volume than that of the pristine CPC (UFICPC0). In vitro and in vivo results proved that the introduction of ultrafine degradable fibers within a CPC matrix can be used to improve macroporosity efficiently and enhance CPC degradation and bone ingrowth largely.