Anisotropic Superconducting Properties of Kagome Metal CsV_3Sb_5

We systematically measure the superconducting(SC) and mixed state properties of high-quality CsV_3 Sb_5 single crystals with T_c～3.5 K.We find that the upper critical field H_(c2)(T) exhibits a large anisotropic ratio of H_(c2)~(ab)/H_(c2)~c～9 at zero temperature and fitting its temperature dependence requires a minimum two-band effective model.Moreover,the ratio of the lower critical field,H_(c1)~(ab)/H_(c1)~c,is also found to be larger than 1,which indicates that the in-plane energy dispersion is strongly renormalized near Fermi energy.Both H_(c1)(T) and SC diamagnetic signal are found to change little initially below T_c～3.5 K and then to increase abruptly upon cooling to a characteristic temperature of ～2.8 K.Furthermore,we identify a two-fold anisotropy of in-plane angular-dependent magnetoresistance in the mixed state.Interestingly,we find that,below the same characteristic T～2.8 K,the orientation of this two-fold anisotropy displays a peculiar twist by an angle of 60° characteristic of the Kagome geometry.Our results suggest an intriguing superconducting state emerging in the complex environment of Kagome lattice,which,at least,is partially driven by electron-electron correlation.     

Luminescence interference-free lifetime nanothermometry pinpoints in vivo temperature

Luminescence nanothermometry makes non-invasive and real-time temperature readings possible in living animals. However,the spectral fluctuation in tissues and fluids, as well as the interaction between fluorophores and environment hinders accuracy of the thermometry. Here, we report a luminescence lifetime-based nanothermometry which specifically addresses this problem. A temporal based calibration(lifetime sensing) in the NIR range, an endogenous thermal response as well as a polymer encapsulation evading environmental factors, altogether help to pinpoint temperature in vivo. Thanks to the highly condensed NdYb ions in a well-protected tiny core-shell nanocrystal(overall 11 nm), a temperature sensitivity about 2.07% K~(-1)(with 5% Yb~(3+) doped nanoparticles) and an accuracy of 0.27 K(with 25% Yb~(3+) doped nanoparticles) in biological fluids are achieved.Hopefully, combining thermally activated energy transfer nanothermometer with anti-interference lifetime thermometry would provide a more accurate temperature measurement for biological and preclinical studies.     

Interfacial Adhesion between Fatty Acid Collectors and Hydrophilic Surfaces: Implications for Low-Rank Coal Flotation

Fatty acids, which are enriched in vegetable oil, have attracted much attention in low-rank coal flotation because of their unique chemical structure. In this study, density functional theory calculations, molecular dynamics simulations, and atomic force microscopy were employed to investigate the adsorption structure and forces between collectors and hydrophilic surfaces. The results show that fatty acids can be easily adsorbed onto surfaces through hydrogen bonds, and can cover the oxygen sites. The existence of hydration film on hydrophilic surfaces prevented nonpolar molecules from being able to adsorb, while polar fatty acids could adsorb and expel water molecules. The adhesion force between the RCOOH-terminated probe and the surface appeared in the retraction process, which differed significantly from that of the RCH₃-terminated probe, indicating that polar fatty acids are more suitable as flotation collectors for low-rank coal than nonpolar hydrocarbon oil. The simulation and AFM test revealed the mechanisms of polar fatty acids, and can provide guidance for low-rank coal flotation applications.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

Construction of Binary Quantum Error-Correcting Codes from Orthogonal Array

By using difference schemes, orthogonal partitions and a replacement method, some new methods to construct pure quantum error-correcting codes are provided from orthogonal arrays. As an application of these methods, we construct several infinite series of quantum error-correcting codes including some optimal ones. Compared with the existing binary quantum codes, more new codes can be constructed, which have a lower number of terms (i.e., the number of computational basis states) for each of their basis states.     

Intelligent Fault Diagnosis of Industrial Robot Based on Multiclass Mahalanobis-Taguchi System for Imbalanced Data

One of the biggest challenges for the fault diagnosis research of industrial robots is that the normal data is far more than the fault data; that is, the data is imbalanced. The traditional diagnosis approaches of industrial robots are more biased toward the majority categories, which makes the diagnosis accuracy of the minority categories decrease. To solve the imbalanced problem, the traditional algorithm is improved by using cost-sensitive learning, single-class learning and other approaches. However, these algorithms also have a series of problems. For instance, it is difficult to estimate the true misclassification cost, overfitting, and long computation time. Therefore, a fault diagnosis approach for industrial robots, based on the Multiclass Mahalanobis-Taguchi system (MMTS), is proposed in this article. It can be classified the categories by measuring the deviation degree from the sample to the reference space, which is more suitable for classifying imbalanced data. The accuracy, G-mean and F-measure are used to verify the effectiveness of the proposed approach on an industrial robot platform. The experimental results show that the proposed approach’s accuracy, F-measure and G-mean improves by an average of 20.74%, 12.85% and 21.68%, compared with the other five traditional approaches when the imbalance ratio is 9. With the increase in the imbalance ratio, the proposed approach has better stability than the traditional algorithms.     

In Vitro and In Vivo Antibacterial Activity,Toxicity and Resistance Analysis of Pleuromutilin Derivative Z33 against Methicillin-Resistant Staphylococcus aureus

The novel pleuromutilin derivative, which showed excellent in vitro antibacterial activity against MRSA, 22-(2-(2-(4-((4-(4-nitrophenyl)piperazin-1-yl)methyl)-1H-1,2,3-triazol-1-yl)acetamido)phenyl)thioacety-l-yl-22-deoxypleuromutilin (Z33), was synthesized and characterized in our previous work. In this study, the preliminary pharmacodynamics and safety of Z33 were further evaluated. In in vitro antibacterial activity assays, Z33 was found to be a potent bactericidal antibiotic against MRSA that induced dose-dependent growth inhibition and long-term post-antibiotic effect (PAE). The drug-resistance test demonstrated that Z33 possessed a narrow mutant selection window and lower propensities to select resistance than that of tiamulin. Cytochrome P450 (CYP450) inhibition assay determined that the inhibitory effect of Z33 was similar to that of tiamulin against the activity of CYP3A4, and was lower than that of tiamulin on the activity of CYP2E1. Toxicity determination showed that both Z33 and tiamulin displayed low cytotoxicity of RAW264.7 cells. Furthermore, Z33 was found to be a high-security compound with a 50% lethal dose (LD₅₀) above 5000 mg/kg in the acute oral toxicity test in mice. In an in vivo antibacterial activity test, Z33 displayed better therapeutic effectiveness than tiamulin in the neutropenic mouse thigh infection model. In summary, Z33 was worthy of further development as a highly effective and safe antibiotic agent against MRSA infection.     

Synthesis of Halopyrazole Matrine Derivatives and Their Insecticidal and Fungicidal Activities

Matrine is a traditional botanical pesticide with a broad-spectrum biological activity that is widely applied in agriculture. Halopyrazole groups are successfully introduced to the C13 of matrine to synthesize eight new derivatives with a yield of 78–87%. The insecticidal activity results show that the introduction of halopyrazole groups can significantly improve the insecticidal activity of matrine on Plutella xylostella, Mythimna separata and Spodoptera frugiperda with a corrected mortality rate of 100%, which is 25–65% higher than matrine. The fungicidal activity results indicate that derivatives have a high inhibitory effect on Ceratobasidium cornigerum, Cibberella sanbinetti, Gibberrlla zeae and Collectot tichum gloeosporioides. Thereinto, 4-Cl-Pyr-Mat has the best result, with an inhibition rate of 23–33% higher than that of matrine. Therefore, the introduction of halogenated pyrazole groups can improve the agricultural activity of matrine.     

Cardiac-specific overexpression of Ndufs1 ameliorates cardiac dysfunction after myocardial infarction by alleviating mitochondrial dysfunction and apoptosis

Myocardial infarction (MI) is the leading cause of premature death among adults. Cardiomyocyte death and dysfunction of the remaining viable cardiomyocytes are the main pathological factors of heart failure after MI. Mitochondrial complexes are emerging as critical mediators for the regulation of cardiomyocyte function. However, the precise roles of mitochondrial complex subunits in heart failure after MI remain unclear. Here, we show that NADH:ubiquinone oxidoreductase core subunit S1 (Ndufs1) expression is decreased in the hearts of heart failure patients and mice with myocardial infarction. Furthermore, we found that cardiac-specific Ndufs1 overexpression alleviates cardiac dysfunction and myocardial fibrosis in the healing phase of MI. Our results demonstrated that Ndufs1 overexpression alleviates MI/hypoxia-induced ROS production and ROS-related apoptosis. Moreover, upregulation of Ndufs1 expression improved the reduced activity of complex I and impaired mitochondrial respiratory function caused by MI/hypoxia. Given that mitochondrial function and cardiomyocyte apoptosis are closely related to heart failure after MI, the results of this study suggest that targeting Ndufs1 may be a potential therapeutic strategy to improve cardiac function in patients with heart failure.Subject terms: Heart failure, Myocardial infarction, Myocardial infarction     

Nickel-catalyzed cross-electrophile allylation of vinyl bromides and the modification of anti-tumour natural medicine β-elemene

Herein, we present a facile and efficient allylation method via Ni-catalyzed cross-electrophile coupling of readily available allylic acetates with a variety of substituted alkenyl bromides using zinc as the terminal reductant. This Ni-catalyzed modular approach displays excellent functional group tolerance and a broad substrate scope, which the creation of a series of 1,4-dienes including several structurally complex natural products and pharmaceutical motifs. Moreover, the coupling strategy has the potential to realize enantiomeric control. The practicality of this transformation is demonstrated through the potent modification of the naturally antitumor active molecule β-elemene.

Herein, we present a facile and efficient allylation method via Ni-catalyzed cross-electrophile coupling of readily available allylic acetates with a variety of substituted alkenyl bromides using zinc as the terminal reductant.