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.     

Catalyst-and additive-free selective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones leading to sulfonylated γ-butyrolactams

A convenient and regioselective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones has been developed to access a series of sulfonylated γ-butyrolactams.The present reaction could be efficiently conducted under catalyst-and additive-free conditions,in which C-S and C-C bonds were selectively constructed in one-pot procedure.     

An unexpected all-metal aromatic tetranuclear silver cluster in human copper chaperone Atox1

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s¹ electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag₄ cluster is Ag₄²⁺, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.     

Broadband Sheet Parametric Oscillator for x~((2)) Optical Frequency Comb Generation via Cavity Phase Matching

We demonstrate a broadband optical parametric oscillation, using a sheet cavity, via cavity phase-matching. A21.2 THz broad comb-like spectrum is achieved, with a uniform line spacing of 133.0 GHz, despite a relatively large dispersion of 275.4 fs~2/mm around 1064 nm. With 22.6% high slope efficiency, and 14.9 kW peak power handling, this sheet optical parametric oscillator can be further developed for x~((2)) comb.     

Defect Engineering on Boron Nitride for O2 Activation and Subsequent Oxidative Desulfurization

The rational design of highly active hexagonal boron nitride (h-BN) catalysts at the atomic level is urgent for aerobic reactions. Herein, a doping impurity atom strategy is adopted to increase its catalytic activities. A series of doping systems involving O, C impurities and B, N antisites are constructed and their catalytic activities for molecular O₂ have been studied by density functional theory (DFT) calculations. It is demonstrated that O₂ is highly activated on O_N and B_N defects, and moderately activated on C_B and C_N defects, however, it is not stable on N_B and O_B defects. The subsequent application in oxidative desulfurization (ODS) reactions proves the O_N and C-doped (C_B, C_N) systems to be good choice for sulfocompounds oxidization, especially for dibenzothiophene (DBT). While the B_N antisite is not suitable for such aerobic reaction due to the extremely stable B−O^*−B species formed during the oxidation process.     

Crosslinked polyaniline nanorods coupled with molybdenum disulfide on functionalized carbon cloth for excellent electrochemical performance

Journal of Solid State Electrochemistry - In this work, the binary nanocomposite of crosslinked polyaniline nanorods (CPANINRs) and molybdenum disulfide (MoS2) is first synthesized by in situ...     

Mechanically strong and stiff supramolecular polymers enabled by fiber reinforced long-chain alkane matrix

Fiber-reinforced-concrete (FRC) mechanism refers short discrete fibers that are uniformly distributed and randomly oriented, which offers an effective way to improve the mechanical performance of concrete. In the design of supramolecular polymers, an analogous concept of FRC appears to have been considered very rarely-although fibrous structure has been frequently observed/generated during the supramolecular polymerization. In this work, we apply the alkane thermosets, octadecane (C₁₈H₃₈) and tetracosane (C₂₄H₅₀), taking the role of “concrete”, and the low-molecular-weight monomer with long alkyl chains as the essential “fiber” component, to fabricate the “fiber reinforced supramolecular polymer”. Very much like FRC mechanism in material science, the resulting fiber reinforced supramolecular polymer thus exhibit unusually high mechanical strength and stiffness, which is unprecedented in the conventional supramolecular strategy.     

Dithienylmaleimide-based D-A Conjugated Polymer Film: Photo-Responsive Behavior and Application in Electrical Memory and Logic Gates

Solid-stated smart polymers responsive to external stimuli have attracted much attention for potential application in the field of photoelectron devices, logic gates, sensor, data storage and security. However, it is a bigger challenge for polymers than that for small molecules in solid state to acquire stimuli-responsive properties, because polymers with high molecular weight are not as easy to change the packing structure as small molecules under external stimulation. Here, a D-A type alternat...     

Rapid and label-free classification of pathogens based on light scattering,reduced power spectral features and support vector machine

The rapid identification of pathogens is crucial in controlling the food quality and safety. The proposed system for the rapid and label-free identification of pathogens is based on the principle of laser scattering from the bacterial microbes. The clinical prototype consists of three parts: the laser beam, photodetectors, and the data acquisition system. The bacterial testing sample was mixed with 10 mL distilled water and placed inside the machine chamber. When the bacterial microbes pass by the laser beam, the scattering of light occurs due to variation in size, shape, and morphology. Due to this reason, different types of pathogens show their unique light scattering patterns. The photo-detectors were arranged at the surroundings of the sample at different angles to collect the scattered light. The photodetectors convert the scattered light intensity into a voltage waveform. The waveform features were acquired by using the power spectral characteristics, and the dimensionality of extracted features was reduced by applying minimal-redundancy-maximal-relevance criterion (mRMR). A support vector machine (SVM) classifier was developed by training the selected power spectral features for the classification of three different bacterial microbes. The resulting average identification accuracies of E. faecalis,E. coli and S. aureus were 99%, 87%, and 94%, respectively. The overall experimental results yield a higher accuracy of 93.6%, indicating that the proposed device has the potential for label-free identification of pathogens with simplicity, rapidity, and cost-effectiveness.     

Screening the Key Region of Sunlight Regulating the Flavonoid Profiles of Young Shoots in Tea Plants (Camellia sinensis L.) Based on a Field Experiment

Both UV and blue light have been reported to regulate the biosynthesis of flavonoids in tea plants; however, the respective contributions of the corresponding regions of sunlight are unclear. Additionally, different tea cultivars may respond differently to altered light conditions. We investigated the responses of different cultivars (‘Longjing 43’, ‘Zhongming 192’, ‘Wanghai 1’, ‘Jingning 1’ and ‘Zhonghuang 2’) to the shade treatments (black and colored nets) regarding the biosynthesis of flavonoids. For all cultivars, flavonol glycosides showed higher sensitivity to light conditions compared with catechins. The levels of total flavonol glycosides in the young shoots of different tea cultivars decreased with the shade percentages of polyethylene nets increasing from 70% to 95%. Myricetin glycosides and quercetin glycosides were more sensitive to light conditions than kaempferol glycosides. The principal component analysis (PCA) result indicated that shade treatment greatly impacted the profiles of flavonoids in different tea samples based on the cultivar characteristics. UV is the crucial region of sunlight enhancing flavonol glycoside biosynthesis in tea shoots, which is also slight impacted by light quality according to the results of the weighted correlation network analysis (WGCNA). This study clarified the contributions of different wavelength regions of sunlight in a field experiment, providing a potential direction for slightly bitter and astringent tea cultivar breeding and instructive guidance for practical field production of premium teas based on light regimes.