Signature of coexistence of superconductivity and ferromagnetism in two-dimensional NbSe\u3csub\u3e2\u3c/sub\u3e triggered by surface molecular adsorption

Ferromagnetism is usually deemed incompatible with superconductivity. Consequently, the coexistence of superconductivity and ferromagnetism is usually observed only in elegantly designed multi-ingredient structures in which the two competing electronic states originate from separate structural components. Here we report the use of surface molecular adsorption to induce ferromagnetism in two-dimensional superconducting NbSe2, representing the freestanding case of the coexistence of superconductivity and ferromagnetism in one two-dimensional nanomaterial. Surface-structural modulation of the ultrathin superconducting NbSe2 by polar reductive hydrazine molecules triggers a slight elongation of the covalent Nb–Se bond, which weakens the covalent interaction and enhances the ionicity of the tetravalent Nb with unpaired electrons, yielding ferromagnetic ordering. The induced ferromagnetic momentum couples with conduction electrons generating unique correlated effects of intrinsic negative magnetoresistance and the Kondo effect. We anticipate that the surface molecular adsorption will be a powerful tool to regulate spin ordering in the two-dimensional paradigm

Formation and Microbial Composition of Biofilms in Drip Irrigation System under Three Reclaimed Water Conditions

As the second source of water for cities, reclaimed water (RW) has become an effective solution to the problem of water scarcity in modern agriculture. However, the formation of biofilm in an RW distribution system seriously affects the performance of the system and has become a technical challenge in RW utilization. In this study, we first showed that several water quality parameters, including five-day biochemical oxygen demand (BOD5), total bacteria count (TB), total nitrogen (TN), and Cl− were the main factors affecting biofilm accumulation in the drip irrigation system (DIS), with the correlation coefficient averaging above 0.85. Second, after 392 to 490 h of system operation, the total biomass and extracellular polymer (EPS) accumulation rate of biofilms increased to a maximum of 0.72 g/m2·h and 0.027g/m2·h, respectively, making this time point a critical point for controlling biofilm accumulation and clogging of the system. Third, we examined changes in biofilm microbial composition over time on Illumina’s MiSeq platform. High throughput sequencing data showed that bacterial community structure and microbial network interaction and modularity changed significantly between 392 and 490 h, resulting in maximum microbial diversity and community richness at 490 h. Spearman correlation analyses between genera revealed that Sphingomonas and Rhodococcus promote biofilm formation due to their hydrophobicity, while Bacillus, Mariniradius, and Arthronema may inhibit biofilm formation due to their antagonistic effects on other genera. In conclusion, this work has clarified the accumulation process and compositional changes of biofilms in agriculture DIS under different RW conditions, which provides a basis for improving RW utilization efficiency and reducing system maintenance costs

Formation and Microbial Composition of Biofilms in Drip Irrigation System under Three Reclaimed Water Conditions

As the second source of water for cities, reclaimed water (RW) has become an effective solution to the problem of water scarcity in modern agriculture. However, the formation of biofilm in an RW distribution system seriously affects the performance of the system and has become a technical challenge in RW utilization. In this study, we first showed that several water quality parameters, including five-day biochemical oxygen demand (BOD5), total bacteria count (TB), total nitrogen (TN), and Cl− were the main factors affecting biofilm accumulation in the drip irrigation system (DIS), with the correlation coefficient averaging above 0.85. Second, after 392 to 490 h of system operation, the total biomass and extracellular polymer (EPS) accumulation rate of biofilms increased to a maximum of 0.72 g/m2·h and 0.027g/m2·h, respectively, making this time point a critical point for controlling biofilm accumulation and clogging of the system. Third, we examined changes in biofilm microbial composition over time on Illumina’s MiSeq platform. High throughput sequencing data showed that bacterial community structure and microbial network interaction and modularity changed significantly between 392 and 490 h, resulting in maximum microbial diversity and community richness at 490 h. Spearman correlation analyses between genera revealed that Sphingomonas and Rhodococcus promote biofilm formation due to their hydrophobicity, while Bacillus, Mariniradius, and Arthronema may inhibit biofilm formation due to their antagonistic effects on other genera. In conclusion, this work has clarified the accumulation process and compositional changes of biofilms in agriculture DIS under different RW conditions, which provides a basis for improving RW utilization efficiency and reducing system maintenance costs

A Text Classification Model via Multi-Level Semantic Features

Text classification is a major task of NLP (Natural Language Processing) and has been the focus of attention for years. News classification as a branch of text classification is characterized by complex structure, large amounts of information and long text length, which in turn leads to a decrease in the accuracy of classification. To improve the classification accuracy of Chinese news texts, we present a text classification model based on multi-level semantic features. First, we add the category correlation coefficient to TF-IDF (Term Frequency-Inverse Document Frequency) and the frequency concentration coefficient to CHI (Chi-Square), and extract the keyword semantic features with the improved algorithm. Then, we extract local semantic features with TextCNN with symmetric-channel and global semantic information from a BiLSTM with attention. Finally, we fuse the three semantic features for the prediction of text categories. The results of experiments on THUCNews, LTNews and MCNews show that our presented method is highly accurate, with 98.01%, 90.95% and 94.24% accuracy, respectively. With model parameters two magnitudes smaller than Bert, the improvements relative to the baseline Bert+FC are 1.27%, 1.2%, and 2.81%, respectively

A Text Classification Model via Multi-Level Semantic Features

Text classification is a major task of NLP (Natural Language Processing) and has been the focus of attention for years. News classification as a branch of text classification is characterized by complex structure, large amounts of information and long text length, which in turn leads to a decrease in the accuracy of classification. To improve the classification accuracy of Chinese news texts, we present a text classification model based on multi-level semantic features. First, we add the category correlation coefficient to TF-IDF (Term Frequency-Inverse Document Frequency) and the frequency concentration coefficient to CHI (Chi-Square), and extract the keyword semantic features with the improved algorithm. Then, we extract local semantic features with TextCNN with symmetric-channel and global semantic information from a BiLSTM with attention. Finally, we fuse the three semantic features for the prediction of text categories. The results of experiments on THUCNews, LTNews and MCNews show that our presented method is highly accurate, with 98.01%, 90.95% and 94.24% accuracy, respectively. With model parameters two magnitudes smaller than Bert, the improvements relative to the baseline Bert+FC are 1.27%, 1.2%, and 2.81%, respectively

Signature of coexistence of superconductivity and ferromagnetism in two-dimensional NbSe\u3csub\u3e2\u3c/sub\u3e triggered by surface molecular adsorption

Ferromagnetism is usually deemed incompatible with superconductivity. Consequently, the coexistence of superconductivity and ferromagnetism is usually observed only in elegantly designed multi-ingredient structures in which the two competing electronic states originate from separate structural components. Here we report the use of surface molecular adsorption to induce ferromagnetism in two-dimensional superconducting NbSe2, representing the freestanding case of the coexistence of superconductivity and ferromagnetism in one two-dimensional nanomaterial. Surface-structural modulation of the ultrathin superconducting NbSe2 by polar reductive hydrazine molecules triggers a slight elongation of the covalent Nb–Se bond, which weakens the covalent interaction and enhances the ionicity of the tetravalent Nb with unpaired electrons, yielding ferromagnetic ordering. The induced ferromagnetic momentum couples with conduction electrons generating unique correlated effects of intrinsic negative magnetoresistance and the Kondo effect. We anticipate that the surface molecular adsorption will be a powerful tool to regulate spin ordering in the two-dimensional paradigm

Functional Characterization and Phenotyping of Protoplasts on a Microfluidics-Based Flow Cytometry

A better understanding of the phenotypic heterogeneity of protoplasts requires a comprehensive analysis of the morphological and metabolic characteristics of many individual cells. In this study, we developed a microfluidic flow cytometry with fluorescence sensor for functional characterization and phenotyping of protoplasts to allow an unbiased assessment of the influence of environmental factors at the single cell level. First, based on the measurement of intracellular homeostasis of reactive oxygen species (ROS) with a DCFH-DA dye, the effects of various external stress factors such as H2O2, temperature, ultraviolet (UV) light, and cadmium ions on intracellular ROS accumulation in Arabidopsis mesophyll protoplasts were quantitatively investigated. Second, a faster and stronger oxidative burst was observed in Petunia protoplasts isolated from white petals than in those isolated from purple petals, demonstrating the photoprotective role of anthocyanins. Third, using mutants with different endogenous auxin, we demonstrated the beneficial effect of auxin during the process of primary cell wall regeneration. Moreover, UV-B irradiation has a similar accelerating effect by increasing the intracellular auxin level, as shown by double fluorescence channels. In summary, our work has revealed previously underappreciated phenotypic variability within a protoplast population and demonstrated the advantages of a microfluidic flow cytometry for assessing the in vivo dynamics of plant metabolic and physiological indices at the single-cell level