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.     

埋地热油管道正常运行的数值模拟研究

对高凝原油管道输送的水力热力问题进行分析研究,掌握管线运行规律,保证管线安全经济运行有着重要意义.本文建立了埋地热油管道正常运行的数学模型,采用非结构化网格和有限容积法对该问题进行了研究,计算结果与实验测量值吻合良好.     

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.     

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.     

NIR TADF emitters and OLEDs: challenges,progress, and perspectives

Near-infrared (NIR) light-emitting materials show excellent potential applications in the fields of military technology, bioimaging, optical communication, organic light-emitting diodes (OLEDs), etc. Recently, thermally activated delayed fluorescence (TADF) emitters have made historic developments in the field of OLEDs. These metal-free materials are more attractive because of efficient reverse intersystem crossing processes which result in promising high efficiencies in OLEDs. However, the development of NIR TADF emitters has progressed at a relatively slower pace which could be ascribed to the difficult promotion of external quantum efficiencies. Thus, increasing attention has been paid to NIR TADF emitters. In this review, the recent progress of NIR TADF emitters has been summarized along with their molecular design strategies and photophysical properties, as well as electroluminescence performance data of their OLEDs, respectively.

This review presents the recent progress of NIR TADF emitters along with their molecular design strategies and photophysical properties, as well as the electroluminescence performance data of the emitters and their OLEDs.     

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.     

The Antioxidant and Hypolipidemic Effects of Mesona Chinensis Benth Extracts

In this study, the antioxidant and hypolipidemic effects of Mesona Chinensis Benth (MCB) extracts were evaluated. Seven fractions (F0, F10, F20, F30, F40, F50 and MTF) were obtained from the MCB ethanol extracts. Compared to the commercial antioxidants (vitamin C), MTF and F30 exhibited higher antioxidant activities in the antiradical activity test and the FRAP assay. The half-inhibition concentration (IC50) for MTF and F30 were 5.323 µg/mL and 5.278 µg/mL, respectively. MTF at 200 µg/mL significantly decreased the accumulation of TG in oleic acid (OA)-induced HepG2 cells and reversed the inhibitory effect of Compound C on AMPK (MTF and F30 significantly increased the glucose utilization of insulin-induced HepG2 cells). In addition, the components of MTF were identified by HPLC-MS, which were caffeic acid, quercetin 3-O-galactoside, isoquercetin, astragalin, rosmarinic acid, aromadendrin-3-O-rutinoside, rosmarinic acid-3-O-glucoside and kaempferol-7-O-glucoside. Through statistical correlations by Simca P software, it was found that the main antioxidant and hypolipidemic components of MCB might be caffeic acid, kaempferol-7-O-glucoside, rosmarinic acid-3-O-glucoside and aromadendrin-3-O-rutinoside, which may play important roles in the AMPK pathway. MTF and F30 in MCB could be potential health products for the treatment of hyperlipidemia.     

Chemical Constituents from the Flowers of Carthamus tinctorius L. and Their Lung Protective Activity

A new flavonoid, saffloflavanside (1), a new sesquiterpene, safflomegastigside (2), and a new amide, saffloamide (3), together with twenty-two known compounds (4–25), were isolated from the flowers of Carthamus tinctorius L. Their structures were determined based on interpretation of their spectroscopic data and comparison with those reported in the literature. The protective effects against lipopolysaccharide (LPS)-stimulated damage on human normal lung epithelial (BEAS-2B) cells of the compounds were evaluated using MTT assay and cellular immunofluorescence assay. The results showed that compounds 2–3, 8–11, and 15–19 exhibited protective effects against LPS-induced damage to BEAS-2B cells. Moreover, compounds 2–3, 8–11, and 15–19 can significantly downregulate the level of nuclear translocation of NF-κB p-p65. In summary, this study revealed chemical constituents with lung protective activity from C. tinctorius, which may be developed as a drug for the treatment of lung injury.