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Feed shortage has hindered the development of the world's livestock industry, and the rational use of non-conventional forages can help resolve this issue. To improve the fermentation quality of Caragana korshinskii silage, this study isolated lactic acid bacteria (LAB) from fresh Caragana korshinskii and silage samples, as alternatives to traditional commercial LAB inoculants. Utilizing Single Molecule, Real-Time (SMRT) sequencing technology and metabolomics analysis, the microbial community structure and metabolome were examined after 60 days of fermentation to elucidate the mechanism by which isolated LAB affect the fermentation quality of Caragana korshinskii silage. After 60 days of ensiling, the dominant microbial population in the silage shifted from harmful bacteria such as Erwinia, Pantoea, and Enterobacter to LAB. Compared to commercial LAB, the isolated Lactiplantibacillus plantarum significantly reduced the microbial diversity of Caragana korshinskii silage. The species composition of LAB became simpler with Lentilactobacillus parakefiri dominating and achieving a higher relative abundance. By down-regulating Butanoate metabolism and the Pentose phosphate pathway and up-regulating the Ascorbate and aldarate metabolism pathway, the isolated Lactiplantibacillus plantarum significantly lowered the pH of the silage, increased the content of water-soluble carbohydrates (WSC) and lactic acid (LA), reduced the neutral detergent fiber content (NDF), and improved in vitro neutral detergent fiber digestibility (IVNDFD), thereby enhancing the fermentation quality of Caragana korshinskii silage. On the other hand, the isolated Limosilactobacillus fermentum had the opposite effect, with its ensiling outcome being less effective than that of commercial LAB. The results of the study indicate that the addition of the isolated Lactiplantibacillus plantarum improved the quality of Caragana korshinskii silage by regulating metabolic pathways and the composition of microbes within the ensiled feed. [ABSTRACT FROM AUTHOR]

The odor of alfalfa (Medicago sativa L.), the most extensively cultivated forage, can interfere with livestock feeding. This study used an electronic nose in conjunction with gas chromatography–mass spectrometry (GC–MS) to examine the quality, volatile organic compounds (VOCs), and metabolic pathways of alfalfa at budding (X), early flowering (C), and full flowering (S) stages. Results showed that terpenoids increased first and then decreased with growth and development, heterocyclic substances decreased continuously, and alcohols and ketones increased. The crude protein and ether extract decreased and were positively correlated with terpenoids, heterocycles, and nitrogen and sulfur compounds, while the dry matter content, soluble carbohydrates, and neutral detergent fiber increased and were positively correlated with alcohols and ketones. The VOCs were most accumulated in the early flowering stages, which had more sweet and fruity flavors, and the main substances that differed from the budding stage and the full flowering stage were methyl heptanoate, butyl butyrate, β-ionone, and other esters and terpenoids. The monoterpene, sesquiterpene, and triterpene pathways were up-regulated in the early flowering stage, and the phenyl-propylene synthesis pathway was up-regulated in the full flowering stage. These substances and pathways were key to further improving alfalfa odor, grade and utilization. [ABSTRACT FROM AUTHOR]

In this study, the chloroplast (cp) genomes of Hemiptelea davidii, Ulmus parvifolia, Ulmus lamellosa, Ulmus castaneifolia, and Ulmus pumila 'zhonghuajinye' were spliced, assembled and annotated using the Illumina HiSeq PE150 sequencing platform, and then compared to the cp genomes of other Ulmus and Ulmaceae species. The results indicated that the cp genomes of the five sequenced species showed a typical tetrad structure with full lengths ranging from 159,113 to 160,388 bp. The large single copy (LSC), inverted repeat (IR), and small single copy (SSC) lengths were in the range of 87,736–88,466 bp, 26,317–26,622 bp and 18,485–19,024 bp, respectively. A total of 130–131 genes were annotated, including 85–86 protein-coding genes, 37 tRNA genes and eight rRNA genes. The GC contents of the five species were similar, ranging from 35.30 to 35.62%. Besides, the GC content was different in different region and the GC content in IR region was the highest. A total of 64-133 single sequence repeat (SSR) loci were identified among all 21 Ulmaceae species. The (A)n and (T)n types of mononucleotide were highest in number, and the lengths were primarily distributed in 10–12 bp, with a clear AT preference. A branch-site model and a Bayes Empirical Bayes analysis indicated that the rps15 and rbcL had the positive selection sites. Besides, the analysis of mVISTA and sliding windows got a lot of hotspots such as trnH/psbA, rps16/trnQ, trnS/trnG, trnG/trnR and rpl32/trnL, which could be utilized as potential markers for the species identification and phylogeny reconstruction within Ulmus in the further studies. Moreover, the evolutionary tree of Ulmaceae species based on common protein genes, whole cp genome sequences and common genes in IR region of the 23 Ulmaceae species were constructed using the ML method. The results showed that these Ulmaceae species were divided into two branches, one that included Ulmus, Zelkova and Hemiptelea, among which Hemiptelea was the first to differentiate and one that included Celtis, Trema, Pteroceltis, Gironniera and Aphananthe. Besides, these variations found in this study could be used for the classification, identification and phylogenetic study of Ulmus species. Our study provided important genetic information to support further investigations into the phylogenetic development and adaptive evolution of Ulmus and Ulmaceae species. [ABSTRACT FROM AUTHOR]

Unsupervised feature learning with deep networks has been widely studied in recent years. Among these networks, deep autoencoders have shown a decent performance in discovering hidden geometric structure of the original data. Both nonnegativity and graph constraints show the effectiveness in representing intrinsic structures in the high dimensional ambient space. This paper combines the nonnegativity and graph constraints to find the original geometrical information intrinsic to high dimensional data, keeping it in a dimensionality reduced space. In the experiments, we test the proposed networks on several standard image data sets. The results demonstrate that they outperform existing methods. [ABSTRACT FROM AUTHOR]

Acoustic metamaterials have become a novel and effective way to control sound waves and design acoustic devices. In this study, we design a 3D acoustic metamaterial lens (AML) to achieve point-to-point acoustic communication in air: any acoustic source (a speaker) in air enclosed by such an AML can produce an acoustic image where the acoustic wave is focused (the field intensity is at a maximum, and the listener can receive the information), while the acoustic field at other spatial positions is low enough that listeners can hear almost nothing. Unlike a conventional elliptical reflective mirror, the acoustic source can be moved around inside our proposed AML. Numerical simulations are given to verify the performance of the proposed AML. [ABSTRACT FROM AUTHOR]

Utilization of visible light is of crucial importance for exploiting efficient semiconductor catalysts for solar water splitting. In this study, an advanced ion implantation method was utilized to dope Cu ions into ZnO nanorod arrays for photoelectrochemical water splitting in visible light. X-ray diffraction (XRD) and X-ray photo-electron spectroscopy (XPS) results revealed that Cu together with a small amount of Cu were highly dispersed within the ZnO nanorod arrays. The Cu ion doped ZnO nanorod arrays displayed extended optical absorption and enhanced photoelectrochemical performance under visible light illumination ( λ > 420 nm). A considerable photocurrent density of 18 μA/cm at 0.8 V (vs. a saturated calomel electrode) was achieved, which was about 11 times higher than that of undoped ZnO nanorod arrays. This study proposes that ion implantation could be an effective approach for developing novel visible-light-driven photocatalytic materials for water splitting. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

At present, the available SSR markers of elm (Ulmus) have been seriously deficient, which can not meet the needs of molecular marker-assisted breeding and evaluation of germplasm resources. In this study, transcriptome data of Ulmus pumila were used as materials to develop EST-SSR markers of elms. EST-SSR markers were also classified according to gene function for the first time. In this study, 8288 perfect and 569 compound SSR loci were detected from 17,624 EST sequences (36,609,384 bp). Most of the perfect SSR sequences were based on short sequence lengths of 10–22 bp. The most common SSR repeat units were A/T (3330, 40.18%), AG/CT (1211, 14.61%), and AAG/CTT (568, 6.85%). All EST-SSR loci were function classified based on the Cluster of Orthologous Groups (COG) database. There were substantial differences in the type and proportion of SSR repeat units among the functional classes. Most EST-SSR loci were located in gene-coding regions. Ninety pairs were randomly selected and tested for validation using polymerase chain reaction amplification. Forty-nine primers were verified with clear bands. The number of alleles per locus (Na) ranged from 2 to 6; the number of effective alleles (Ne) ranged from 1.061 to 3.261; the observational heterozygosity (Ho) and expected heterozygosity (He) ranged from 0 to 0.968 and 0.112 to 0.651, respectively. The clustering pattern is consistent with traditional taxonomy that provides a molecular basis for the classification of elm. There were differences in the effective amplification and percentage of polymorphic loci among different functional SSR loci. The analysis of 880 primer combinations showed that markers within a single COG group were less effective than across groups. This study clarified the importance of SSR primer selection for clustering results. This study developed a large number of SSR markers in elm, providing effective markers for molecular marker-assisted breeding, genetic mapping, and other related research. [ABSTRACT FROM AUTHOR]

Solution-based ZnO nanorod arrays (NRAs) were modified with controlled N doping by an advanced ion implantation method, and were subsequently utilized as photoanodes for photoelectrochemical (PEC) water splitting under visible light irradiation. A gradient distribution of N dopants along the vertical direction of ZnO nanorods was realized. N doped ZnO NRAs displayed a markedly enhanced visible-light-driven PEC photocurrent density of ~160 μA/cm2 at 1.1 V vs. saturated calomel electrode (SCE), which was about 2 orders of magnitude higher than pristine ZnO NRAs. The gradiently distributed N dopants not only extended the optical absorption edges to visible light region, but also introduced terraced band structure. As a consequence, N gradient-doped ZnO NRAs can not only utilize the visible light irradiation but also efficiently drive photo-induced electron and hole transfer via the terraced band structure. The superior potential of ion implantation technique for creating gradient dopants distribution in host semiconductors will provide novel insights into doped photoelectrode materials for solar water splitting. [ABSTRACT FROM AUTHOR]