525 research outputs found

    The genome evolution and domestication of tropical fruit mango

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    Background: Mango is one of the world’s most important tropical fruits. It belongs to the family Anacardiaceae, which includes several other economically important species, notably cashew, sumac and pistachio from other genera. Many species in this family produce family-specific urushiols and related phenols, which can induce contact dermatitis. Results: We generate a chromosome-scale genome assembly of mango, providing a reference genome for the Anacardiaceae family. Our results indicate the occurrence of a recent whole-genome duplication (WGD) event in mango. Duplicated genes preferentially retained include photosynthetic, photorespiration, and lipid metabolic genes that may have provided adaptive advantages to sharp historical decreases in atmospheric carbon dioxide and global temperatures. A notable example of an extended gene family is the chalcone synthase (CHS) family of genes, and particular genes in this family show universally higher expression in peels than in flesh, likely for the biosynthesis of urushiols and related phenols. Genome resequencing reveals two distinct groups of mango varieties, with commercial varieties clustered with India germplasms and demonstrating allelic admixture, and indigenous varieties from Southeast Asia in the second group. Landraces indigenous in China formed distinct clades, and some showed admixture in genomes. Conclusions: Analysis of chromosome-scale mango genome sequences reveals photosynthesis and lipid metabolism are preferentially retained after a recent WGD event, and expansion of CHS genes is likely associated with urushiol biosynthesis in mango. Genome resequencing clarifies two groups of mango varieties, discovers allelic admixture in commercial varieties, and shows distinct genetic background of landraces

    Coordinated Speed Control Strategy for Minimizing Energy Consumption of a Shearer in Fully Mechanized Mining

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    As one of the major pieces of equipment in fully mechanized coal mining, the drum shearer plays a critical role in improving the efficiency and energy utilization in the coal mining production process. In this paper, an energy consumption model of a shearer, derived from the analysis of the cutting and traction resistances on the shearer during different processes within a working cycle, is established. Based on the derived model, control and coordination strategies between the two speeds are proposed to minimize the shearer’s energy consumption in unidirectional mining. The case study of a real coal mine shows that the proposed models are valid, and the optimal control of shearer speeds can effectively reduce the energy consumption by 5.16% in a working cycle. To gain further insights into the impact of traction speed and drum rotational speed on the shearer’s energy consumption, several speed coordination cases are employed to further compare with the optimized one. Our study results show that the energy consumption of a shearer can be decreased with the increase of traction speed while decreasing drum rotational speed in coordination

    Joint Resources and Workflow Scheduling in UAV-Enabled Wirelessly-Powered MEC for IoT Systems

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    This paper considers a UAV-enabled mobile edge computing (MEC) system, where a UAV first powers the Internet of things device (IoTD) by utilizing Wireless Power Transfer (WPT) technology. Then each IoTD sends the collected data to the UAV for processing by using the energy harvested from the UAV. In order to improve the energy efficiency of the UAV, we propose a new time division multiple access (TDMA) based workflow model, which allows parallel transmissions and executions in the UAV-assisted system. We aim to minimize the total energy consumption of the UAV by jointly optimizing the IoTDs association, computing resources allocation, UAV hovering time, wireless powering duration and the services sequence of the IoTDs. The formulated problem is a mixed-integer non-convex problem, which is very difficult to solve in general. We transform and relax it into a convex problem and apply flow-shop scheduling techniques to address it. Furthermore, an alternative algorithm is developed to set the initial point closer to the optimal solution. Simulation results show that the total energy consumption of the UAV can be effectively reduced by the proposed scheme compared with the conventional systems

    Divergent adaptations of leaf functional traits to light intensity across common urban plant species in Lanzhou, northwestern China

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    Leaves are the most important photosynthetic organs in plants. Understanding the growth strategy of leaves in different habitats is crucial for elucidating the mechanisms underlying plant response and adaptation to the environment change. This study investigated the scaling relationships of the laminar area (LA), leaf fresh mass (LFM), leaf dry mass (LDM), and explored leaf nitrogen (N) and phosphorus (P) content in leaves, and the relative benefits of these pairwise traits in three common urban plants (Yulania denudata, Parthenocissus quinquefolia, and Wisteria sinensis) under different light conditions, including (full-sun and canopy-shade). The results showed that: the scaling exponent of LDM vs LA (> 1, p < 0.05) meant that the LDM increased faster than LA, and supported the hypothesis of diminishing returns. The LFM and LDM had isometric relationships in all the three species, suggesting that the leaf water content of the leaves was nearly unaltered during laminar growth. Y. denudata and W. sinensis had higher relative benefit in full-sun habitats, while the reverse was observed in P. quinquefolia. The N and P content and the N:P ratio in full-sun leaves were generally higher than those of canopy-shade leaves. The leaves of the three urban plants exhibited a shift in strategy during transfer from the canopy shaded to the sunny habitat for adapting to the lower light conditions. The response of plant leaves to the environment shapes the rich variations at the leaf level, and quantification of the relative benefits of plants in different habitats provides novel insights into the response and adaptation strategies of plants

    Efficient generation of HPLC and FTIR data for quality assessment using time series generation model: a case study on Tibetan medicine Shilajit

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    BackgroundThe scarcity and preciousness of plateau characteristic medicinal plants pose a significant challenge in obtaining sufficient quantities of experimental samples for quality evaluation. Insufficient sample sizes often lead to ambiguous and questionable quality assessments and suboptimal performance in pattern recognition. Shilajit, a popular Tibetan medicine, is harvested from high altitudes above 2000 m, making it difficult to obtain. Additionally, the complex geographical environment results in low uniformity of Shilajit quality.MethodsTo address these challenges, this study employed a deep learning model, time vector quantization variational auto- encoder (TimeVQVAE), to generate data matrices based on chromatographic and spectral for different grades of Shilajit, thereby increasing in the amount of data. Partial least squares discriminant analysis (PLS-DA) was used to identify three grades of Shilajit samples based on original, generated, and combined data.ResultsCompared with the originally generated high performance liquid chromatography (HPLC) and Fourier transform infrared spectroscopy (FTIR) data, the data generated by TimeVQVAE effectively preserved the chemical profile. In the test set, the average matrices for HPLC, FTIR, and combined data increased by 32.2%, 15.9%, and 23.0%, respectively. On the real test data, the PLS-DA model’s classification accuracy initially reached a maximum of 0.7905. However, after incorporating TimeVQVAE-generated data, the accuracy significantly improved, reaching 0.9442 in the test set. Additionally, the PLS-DA model trained with the fused data showed enhanced stability.ConclusionThis study offers a novel and effective approach for researching medicinal materials with small sample sizes, and addresses the limitations of improving model performance through data augmentation strategies

    Accelerated evolution of an Lhx2 enhancer shapes mammalian social hierarchies.

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    Social hierarchies emerged during evolution, and social rank influences behavior and health of individuals. However, the evolutionary mechanisms of social hierarchy are still unknown in amniotes. Here we developed a new method and performed a genome-wide screening for identifying regions with accelerated evolution in the ancestral lineage of placental mammals, where mammalian social hierarchies might have initially evolved. Then functional analyses were conducted for the most accelerated region designated as placental-accelerated sequence 1 (PAS1, P = 3.15 × 10-18). Multiple pieces of evidence show that PAS1 is an enhancer of the transcription factor gene Lhx2 involved in brain development. PAS1s isolated from various amniotes showed different cis-regulatory activity in vitro, and affected the expression of Lhx2 differently in the nervous system of mouse embryos. PAS1 knock-out mice lack social stratification. PAS1 knock-in mouse models demonstrate that PAS1s determine the social dominance and subordinate of adult mice, and that social ranks could even be turned over by mutated PAS1. All homozygous mutant mice had normal huddled sleeping behavior, motor coordination and strength. Therefore, PAS1-Lhx2 modulates social hierarchies and is essential for establishing social stratification in amniotes, and positive Darwinian selection on PAS1 plays pivotal roles in the occurrence of mammalian social hierarchies

    The genome evolution and domestication of tropical fruit mango

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    Background: Mango is one of the world’s most important tropical fruits. It belongs to the family Anacardiaceae, which includes several other economically important species, notably cashew, sumac and pistachio from other genera. Many species in this family produce family-specific urushiols and related phenols, which can induce contact dermatitis. Results: We generate a chromosome-scale genome assembly of mango, providing a reference genome for the Anacardiaceae family. Our results indicate the occurrence of a recent whole-genome duplication (WGD) event in mango. Duplicated genes preferentially retained include photosynthetic, photorespiration, and lipid metabolic genes that may have provided adaptive advantages to sharp historical decreases in atmospheric carbon dioxide and global temperatures. A notable example of an extended gene family is the chalcone synthase (CHS) family of genes, and particular genes in this family show universally higher expression in peels than in flesh, likely for the biosynthesis of urushiols and related phenols. Genome resequencing reveals two distinct groups of mango varieties, with commercial varieties clustered with India germplasms and demonstrating allelic admixture, and indigenous varieties from Southeast Asia in the second group. Landraces indigenous in China formed distinct clades, and some showed admixture in genomes. Conclusions: Analysis of chromosome-scale mango genome sequences reveals photosynthesis and lipid metabolism are preferentially retained after a recent WGD event, and expansion of CHS genes is likely associated with urushiol biosynthesis in mango. Genome resequencing clarifies two groups of mango varieties, discovers allelic admixture in commercial varieties, and shows distinct genetic background of landraces
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