Orbital density wave induced by electron-lattice coupling in orthorhombic iron pnictides

In this paper we explore the magnetic and orbital properties closely related to a tetragonal-orthorhombic structural phase transition in iron pnictides based on both two- and five-orbital Hubbard models. The electron-lattice coupling, which interplays with electronic interaction, is self-consistently treated. Our results reveal that the orbital polarization stabilizes the spin density wave (SDW) order in both tetragonal and orthorhombic phases. However, the ferro-orbital density wave (F-ODW) only occurs in the orthorhombic phase rather than in the tetragonal one. Magnetic moments of Fe are small in the intermediate Coulomb interaction region for the striped antiferromangnetic phase in the realistic five orbital model. The anisotropic Fermi surface in the SDW/ODW orthorhombic phase is well in agreement with the recent angle-resolved photoemission spectroscopy experiments. These results suggest a scenario that the magnetic phase transition is driven by the ODW order mainly arising from the electron-lattice coupling.Comment: 21 pages, 10 figure

Multi-point geostatistics for ore grade estimation

A multi-point geostatistical method for ore grade estimation is introduced in order to fully utilize existing sampling information. A block model is used to construct a new three-dimensional training image instead of a variogram. Data events and pattern matching is improved, and the directionality of the data template is considered in the matching. The inverse distance weighted method is used to make up for the lack of multi-point geostatistics. The research improves the reliability of multi-point geostatistical estimation. Optimal estimation results for Li2O and Ta2O5 come from the inverse distance weighted, ordinary Kriging, and multi-point geostatistical methods. Multi-point geostatistical estimation results are compared with those of the inverse distance weighted and ordinary Kriging methods. Deviation, trend, and variogram analyses are used to assess the effect of multipoint geostatistical estimation. This study shows that reducing the samples participating in the estimation can reduce the maximum and minimum deviation of the estimated grade to a certain extent. The grade distribution pattern is the primary factor affecting minimum and maximum deviation. This study proves the reliability and accuracy of the multi-point geostatistical method for ore grade estimation.</p

Heterogeneous impact of artificial intelligence on carbon emission intensity: Empirical test based on provincial panel data in China

IntroductionEnergy conservation and emission reduction, as a major policy of China for a long time, has been put on the key strategic position. Based on the panel data of 30 provinces, cities and districts in China from 2006 to 2019.MethodsThis paper uses fixed effect model and spatial Durbin model to explore the effect and mechanism of artificial intelligence (AI) on regional carbon emission intensity (CEI).ResultsThe results show that: (1) there is a significant inverted U-shaped between AI and CEI, that is, with the deepening of the development of AI, CEI first increases and then decreases. (2) There is a significant spatial correlation between the development of AI and CEI in China. (3) AI has a significant spatial spillover effect on CEI of adjacent regions, and it shows an inverted U-shaped track-from promoting to restraining.DiscussionThe conclusion provides policy implications for the formulation of AI development strategy and so on during the specific period

A combination network of CNN and transformer for interference identification

Communication interference identification is critical in electronic countermeasures. However, existed methods based on deep learning, such as convolutional neural networks (CNNs) and transformer, seldom take both local characteristics and global feature information of the signal into account. Motivated by the local convolution property of CNNs and the attention mechanism of transformer, we designed a novel network that combines both architectures, which make better use of both local and global characteristics of the signals. Additionally, recognizing the challenge of distinguishing contextual semantics within the one-dimensional signal data used in this study, we advocate the use of CNNs in place of word embedding, aligning more closely with the intrinsic features of the signal data. Furthermore, to capture the time-frequency characteristics of the signals, we integrate the proposed network with a cross-attention mechanism, facilitating the fusion of temporal and spectral domain feature information through multiple cross-attention computational layers. This innovation obviates the need for specialized time-frequency analysis. Experimental results demonstrate that our approach significantly improves recognition accuracy compared to existing methods, highlighting its efficacy in addressing the challenge of communication interference identification in electronic warfare

Separation and economic recovery of strontium from Nanyishan oil-field water, China

The mass ratio of Ca to Sr is greater than 10 in Nanyishan oil-field water, which causes significant problems during the economic extraction and recovery of selected trace elements in the oil-field water. The oilfield water was isothermally evaporated and various salts such as Li, K, Mg, Ca, Na, Sr, Rb, Cs, Br, and I were obtained from the solution. The Sr content of each phase was determined by ICP-AES, the Sr distribution rule in this process was obtained, and the best separation stage for Sr was identified, to optimize the separation of Sr from Nanyishan oil-field water

MALDI-TOF MS Analysis of Condensed Tannins with Potent Antioxidant Activity from the Leaf, Stem Bark and Root Bark of Acacia confusa

The structures of the condensed tannins from leaf, stem bark and root bark of Acacia confusa were characterized by matrix-assisted laser desorption/ionization time-off-light mass spectrometry (MALDI-TOF MS) analysis, and their antioxidant activities were measured using 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging and ferric reducing/antioxidant power (FRAP) assays. The results showed that the condensed tannins from stem bark and root bark include propelargonidin and procyanidin, and the leaf condensed tannins include propelargonidin, procyanidin and prodelphinidin, all with the procyanidin dominating. The condensed tannins had different polymer chain lengths, varying from trimers to undecamers for leaf and root bark and to dodecamers for stem bark. The condensed tannins extracted from the leaf, stem bark and root bark all showed a very good DPPH radical scavenging activity and ferric reducing power.Program for New Century Excellent Talents in University [NCET-07-0725]; Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministr