次级源和误差传感器布放对带弹性障板的充液直管声振复合有源控制的影响*

针对充液管路系统噪声有源控制问题,研究了次级源和误差传感器布放对带弹性障板的充液直管管路系统有源消声与有源消振复合控制效果的影响。基于声固耦合方法建立了带弹性障板的充液直管管路系统的有限元模型,在声激励下对比了次级声源布放对系统有源消声性能的影响,并在组合激励下分析了次级力源、次级声源和误差传感器布放对系统复合有源控制的影响。结果表明,非对称分布的次级声源容易激起管壁振动,进而带动障板振动,导致有源消声效果不佳;采用对称分布的次级声源可使低频段的降噪量提高10 dB以上。复合有源控制可进一步提升全频段的控制效果。通过增加振动误差传感器数量,可使绝大多数频点的降噪量提高1~20 dB不等。此外,在管壁上布放的两圈次级力源的间距小于管壁振动波长的1/4,且都不位于管壁振动节点附近时控制效果更好。     

A Novel Strategy for Regulating mRNA’s Degradation via Interfering the AUF1’s Binding to mRNA

The study on the mechanism and kinetics of mRNA degradation provides a new vision for chemical intervention on protein expression. The AU enrichment element (ARE) in mRNA 3′-UTR can be recognized and bound by the ARE binding protein (AU-rich Element factor (AUF1) to recruit RNase for degradation. In the present study, we proposed a novel strategy for expression regulation that interferes with the AUF1-RNA binding. A small-molecule compound, JNJ-7706621, was found to bind AUF1 protein and inhibit mRNA degradation by screening the commercial compound library. We discovered that JNJ-7706621 could inhibit the expression of AUF1 targeted gene IL8, an essential pro-inflammatory factor, by interfering with the mRNA homeostatic state. These studies provide innovative drug design strategies to regulate mRNA homeostasis.     

Designable assembly of atomically precise Al4O4 cubane supported mesoporous heterometallic architectures

Heterometallic cluster-based framework materials are of interest in terms of both their porous structures and multi-metallic reactivity. However, such materials have not yet been extensively investigated because of difficulties in their synthesis and structural characterization. Herein, we reported the designable synthesis of atomically precise heterometallic cluster-based framework compounds and their application as catalysts in aldol reactions. By using the synergistic coordination protocol, we successfully isolated a broad range of compounds with the general formula, [Al₄M₄O₄(L)₁₂(DABCO)₂] (L = carboxylates; DABCO = 1,4-diazabicyclo[2.2.2]-octane; M²⁺ = Co²⁺, Mn²⁺, Zn²⁺, Fe²⁺, Cd²⁺). The basic heterometallic building blocks contain unprecedented main-group γ-alumina moieties and surrounding unsaturated transition metal centers. Interestingly, the porosity and interpenetration of these frameworks can be rationally regulated through the unprecedented strategy of increment of the metal radius in addition to general introduction of sterically bulky groups on the ligand. Furthermore, these porous materials are effective catalysts for aldol reactions. This work provides a catalytic molecular model platform with accurate molecular bonding between the supporters and catalytically active metal ions.

Mesoporous heterometallic architectures are designed by the incorporation of the Al₄O₄ cubane and interpenetration regulation.     

Multi-Classifier Fusion Based on MI–SFFS for Cross-Subject Emotion Recognition

With the widespread use of emotion recognition, cross-subject emotion recognition based on EEG signals has become a hot topic in affective computing. Electroencephalography (EEG) can be used to detect the brain’s electrical activity associated with different emotions. The aim of this research is to improve the accuracy by enhancing the generalization of features. A Multi-Classifier Fusion method based on mutual information with sequential forward floating selection (MI_SFFS) is proposed. The dataset used in this paper is DEAP, which is a multi-modal open dataset containing 32 EEG channels and multiple other physiological signals. First, high-dimensional features are extracted from 15 EEG channels of DEAP after using a 10 s time window for data slicing. Second, MI and SFFS are integrated as a novel feature-selection method. Then, support vector machine (SVM), k-nearest neighbor (KNN) and random forest (RF) are employed to classify positive and negative emotions to obtain the output probabilities of classifiers as weighted features for further classification. To evaluate the model performance, leave-one-out cross-validation is adopted. Finally, cross-subject classification accuracies of 0.7089, 0.7106 and 0.7361 are achieved by the SVM, KNN and RF classifiers, respectively. The results demonstrate the feasibility of the model by splicing different classifiers’ output probabilities as a portion of the weighted features.     

Amphotericin B and Curcumin Co-Loaded Porous Microparticles as a Sustained Release System against Candida albicans

Amphotericin B (AMB) is an antifungal drug used for serious fungal infections. However, AMB has adverse reactions such as nephrotoxicity, which limit the clinical application of AMB alone or in combination with other antifungal drugs. Nano or micro drug delivery systems (DDS) have been proven to be effective in reducing the toxic and side effects of drugs. Further, the combination of AMB with other compounds with antifungal activity, such as curcumin (CM), may enhance the synergistic effects. Herein, AMB and CM were co-loaded into porous poly (lactic-co-glycolic acid) (PLGA) microparticles (MPs) to prepare AMB/CM-PLGA MPs. The AMB/CM-PLGA MPs showed a remarkably reduced hemolysis (62.2 ± 0.6%) compared to AMB (80.9 ± 1.1%). The nephrotoxicity of AMB/CM-PLGA MPs is significantly lower than that of AMB. In vitro, AMB/CM-PLGA MPs had better inhibitory effects on the adhesion and biofilm formation of Candida albicans compared with AMB. Experiments on mice infected with C. albicans showed that AMB/CM-PLGA MPs have a better therapeutic effect than AMB in vivo. In summary, AMB/CM-PLGA MPs may be a novel and promising therapeutic candidate for fungal infection.     

The Effects of Charged Amino Acid Side-Chain Length on Diagonal Cross-Strand Interactions between Carboxylate- and Ammonium-Containing Residues in a β-Hairpin

The β-sheet is one of the common protein secondary structures, and the aberrant aggregation of β-sheets is implicated in various neurodegenerative diseases. Cross-strand interactions are an important determinant of β-sheet stability. Accordingly, both diagonal and lateral cross-strand interactions have been studied. Surprisingly, diagonal cross-strand ion-pairing interactions have yet to be investigated. Herein, we present a systematic study on the effects of charged amino acid side-chain length on a diagonal ion-pairing interaction between carboxylate- and ammonium-containing residues in a β-hairpin. To this end, 2D-NMR was used to investigate the conformation of the peptides. The fraction folded population and the folding free energy were derived from the chemical shift data. The fraction folded population for these peptides with potential diagonal ion pairs was mostly lower compared to the corresponding peptide with a potential lateral ion pair. The diagonal ion-pairing interaction energy was derived using double mutant cycle analysis. The Asp2-Dab9 (Asp: one methylene; Dab: two methylenes) interaction was the most stabilizing (−0.79 ± 0.14 kcal/mol), most likely representing an optimal balance between the entropic penalty to enable the ion-pairing interaction and the number of side-chain conformations that can accommodate the interaction. These results should be useful for designing β-sheet containing molecular entities for various applications.     

Structural Characteristics,Antioxidant and Hypoglycemic Activities of Polysaccharide from Siraitia grosvenorii

The structural characterization, the in vitro antioxidant activity, and the hypoglycemic activity of a polysaccharide (SGP-1-1) isolated from Siraitia grosvenorii (SG) were studied in this paper. SGP-1-1, whose molecular weight is 19.037 kDa, consisted of Gal:Man:Glc in the molar ratio of 1:2.56:4.90. According to the results of methylation analysis, GC–MS, and NMR, HSQC was interpreted as a glucomannan with a backbone composed of 4)-β-D-Glcp-(1→4)-, α-D-Glcp-(1→4)-, and 4)-Manp-(1 residues. α-1,6 linked an α-D-Galp branch, and α-1,6 linked an α-D-Glcp branch. The study indirectly showed that SGP-1-1 has good in vitro hypoglycemic and antioxidant activities and that these activities may be related to the fact that the SGP-1-1’s monosaccharide composition (a higher proportion of Gal and Man) is the glycosidic-bond type (α- and β-glycosidic bonds). SGP-1-1 could be used as a potential antioxidant and hypoglycemic candidate for functional and nutritional food applications.     

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.     

Comparison of Fatty Acid Contents and MMP-1 Inhibitory Effects of the Two Antarctic Fish,Notothenia rossii and Champsocephalus gunnari

Total fatty-acid (FA) contents of different organs (stomach, liver, brain, and skin) of two Antarctic fish, marbled rockcod (Notothenia rossii) and mackerel icefish (Champsocephalus gunnari), were examined using gas chromatography–mass spectrometry (GC–MS). N. rossii possessed higher contents of total omega-3, where eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), the most represented omega-3 FAs, were distributed throughout all parts of the fish. The highest level of EPA was observed in the skin and that of DHA was observed in the brain of N. rossii. C. gunnari showed organ peculiarity in that most of the omega-3 FAs were found in stomach and skin. Specifically, the highest levels of EPA and DHA were both observed in the stomach. Although N. rossii and C. gunnari both inhabit the Antarctic Southern Oceans, their characteristics in terms of the composition of fatty acids were shown to vary. The extracts were also evaluated for matrix metalloproteinase-1 (MMP-1)-inhibitory activities in UVB-induced human dermal fibroblasts, where extracts of the skin and liver of N. rossii showed the most significant inhibition upon MMP-1 production. These findings provide experimental evidence that the extracts of the Antarctic fish could be utilized as bioactive nutrients, particularly in the enhancement of skin health.     

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.