Transformer-based models are dominating the field of natural language processing and are becoming increasingly popular in the field of computer vision. However, the black box characteristics of transformers seriously ...
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Lithium-based electrides with interstitial anionic electrons (IAEs) have recently garnered a great deal of attention, since these materials were found to host intriguing properties such as multiple IAE arrangements an...
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Lithium-based electrides with interstitial anionic electrons (IAEs) have recently garnered a great deal of attention, since these materials were found to host intriguing properties such as multiple IAE arrangements and potential superconductivity. In this study, we here conducted comprehensive simulations on the pressure-induced stable Li-abundant germanides leveraging the advanced first-principles structure predictions. As a consequence, our simulations identified several metallic Li-Ge electride phases with robust stability, i.e., Li5Ge, Li6Ge, Li7Ge, Li8Ge, and Li10Ge. Strikingly, the evolution from connected one-dimensional (1D) to zero-dimensional (0D) electride states of Li5Ge was identified concurrent with an orthorhombic Cmcm to triclinic C2/c phase transition on account of compression-induced volume reduction, whereas Li10Ge possesses the unusual coexistent 0D and 1D IAEs. Electron-phonon coupling (EPC) calculations uncover that the superconductivity of Cmcm Li5Ge is superior to that of C2/c Li5Ge at 50 GPa, which is due to the larger EPC strength, higher density of states at the Fermi level, and more pronounced softened phonon modes of Cmcm Li5Ge. Remarkably, Li10Ge was calculated to have the highest superconducting critical temperature (Tc) of 8.5 K below 50 GPa compared to other lithium-carbon family electrides, which is ascribed to the fact that the Li 2p electron states near the Fermi energy are strongly coupled with phonon modes associated with the vibrations of Li atoms. Our findings provide insights into lithium-bearing electride systems with implications for the pursuit of distinguished electride superconductors.
Population initialization is always needed in evolutionary multi-objective optimization (EMO) algorithms. Intuitively, a well-designed initialization method can help facilitate the evolutionary process and improve the...
The exploration of computer vision applications for fabric defect detection has immense potential ***,current relevant research in this area has primarily focused on detection models that aim for high detection accura...
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The exploration of computer vision applications for fabric defect detection has immense potential ***,current relevant research in this area has primarily focused on detection models that aim for high detection accuracy and algorithmic efficiency,while neglecting the practical industrial production ***,we propose a fabric defect detection and post-processing system that integrates an optimized region with convolutional neural network(CNN)features(i.e.,Faster R-CNN)for defect detection,defect localization and detection model *** addition,the proposed intelligent system incorporates novel approaches,such as a rearranged fabric dataset,anomaly detection,recommended clipping region division,and a replenishment *** study illustrates an example of artificial intelligence(AI)-driven automated technology in fabric *** accuracy and detection speed of different detection models under identical hardware conditions are evaluated and compared with related *** results demonstrate that the proposed approach achieves comparable performance to other models,while significantly reducing computational resource *** potential efficiency of using two-stage networks on hardware systems for fabric defect detection tasks is highlighted,which is likely to have relevant implications for the textile industry.
Microbially mediated carbon cycling is essential for the production of refractory dissolved organic carbon and subsequent formation of stable carbon sinks at the sediment–water interface (SWI) in aquatic ecosystems, ...
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Microbially mediated carbon cycling is essential for the production of refractory dissolved organic carbon and subsequent formation of stable carbon sinks at the sediment–water interface (SWI) in aquatic ecosystems, such as lakes. It remains unclear how this process is influenced by hydrostatic pressure changes due to water level fluctuation in deep-water reservoirs. Here, a microcosm simulation experiment was carried out to decipher the response of microbially mediated carbon cycling to various hydrostatic pressures (i.e., 0.1 MPa [atmospheric pressure], 0.2 MPa, 0.5 MPa, 0.7 MPa) at the SWI in Jinpen Reservoir, Shaanxi Province, China. The response mechanisms of microbial community structure, functional gene abundance, and metabolic pathway activity associated with carbon cycling were explored by metagenomics and metabolomics. Results showed that the number of microbial species in sediment samples increased with elevating pressure. The relative abundance of archaea also increased from 0.2% to 0.4% as a consequence of pressure elevation, accompanied by 0.17% and 0.03% decrease in bacteria and fungi, respectively. In contrast with low pressures, high pressures allowed the microbial communities to form a more closely connected network, which maintained more complex interspecies interactions and greater system stability. High pressures additionally improved the abundances of specific functional genes (e.g., ALDO, ACO, sdhA, and sdhC) in carbon metabolic pathways, promoted carbon fixation by the reductive pentose phosphate (Calvin) and citrate cycles, and hindered methanogenesis. Piezophilic taxa (e.g., Gammaproteobacteria, Alphaproteobacteria, Bacteroidetes) and genes (e.g., ompH, asd) were identified among carbon cycling-associated microbial communities. The piezophilic genes, which were mainly present in the Proteobacteria phylum, increased first and then decreased in abundance with elevating pressure. The findings indicate that elevated hydrostatic pressure contrib
作者：
Liu, ShuangLi, YingJilin University
College of Computer Science and Technology Jilin Changchun130012 China Jilin University
Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin Changchun130012 China
The detection of drivable areas holds immense significance within the perception system of autonomous vehicles. This capability enables intelligent vehicles to gain a comprehensive understanding of the current road co...
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A long-standing question in the evolutionary multi-objective (EMO) community is how to generate a good initial population for EMO algorithms. Intuitively, as the starting point of optimization, a good initial populati...
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In the context of industrial automation and intelligent monitoring, accurate identification of the industrial environment is crucial to risk management. However, traditional scene classification methods struggle to ca...
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This paper presents a robust point cloud optimization algorithm based on spatial geometry relationship and Siamese Network. The proposed algorithm is designed to be improve the integrity and accuracy of stereo matchin...
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Designing structured materials with optimized mechanical properties generally focuses on engineering microstructures,which are closely determined by the processing routes,such as phase transformations(PTs)and plastic ...
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Designing structured materials with optimized mechanical properties generally focuses on engineering microstructures,which are closely determined by the processing routes,such as phase transformations(PTs)and plastic deformations(PDs).Both PTs and PDs follow inherent trade-off relation between thermodynamic driving force ΔG and kinetic energy barrier Q,i.e.,so-called thermo-kinetic *** analyzing nucleation and growth and proposing a conception of negative driving force integrating strain energy,interface energy and any kind of energy that equivalently inhibits the PT itself,ΔG^(S),unified expressions for the thermo-kinetic correlation and generalized stability(GS)were derived for three kinds of PTs,i.e.,diffusive PTs with simultaneously decreasedΔG and increased Q,diffusive PTs with simultaneously increasedΔG and decreased Q,and displacive PTs with simultaneously increased ΔG and decreased *** leads to so-called thermo-kinetic connectivity by integrating the thermo-kinetic correlation and the GS,where,by application in typical PTs,it was clearly shown,a criterion of high ΔG-high GS can be predicted by modulating chemical driving force,negative driving force and kinetic energy barrier for diffusion or *** thermo-kinetic connectivity,analogous procedure for dislocation evolution upon PDs was performed,and materials design in terms of the highΔG-high GS criterion was discussed and prospected.
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