Ligand Design in Atomically Precise Copper Nanoclusters and Their Application in Electrocatalytic Reactions

Metal nanoclusters (MNCs) are compositionally well-defined and also structurally precise materials with unique molecule-like properties and discrete electronic energy levels. Atomically precise ligand-protected Cu nanoclusters (LP-CuNCs) are one category of typical MNCs that usually demonstrate unique geometric and electronic structures to serve as electrocatalysts. However, the synthesis, application, as well as structure-performance relationship of LP-CuNCs are not adequately studied. Significantly, the ligands are essential to the geometric structure, crystal structure, size, and electronic structure of LP-CuNCs, which determine their physiochemical properties and applications. In this review, significant progress in the ligand design of LP-CuNCs, and their application in electrocatalytic reactions is introduced. The general basics of ligand-protected MNCs (LP-MNCs) are first introduced and the functions of ligands are emphasized. Subsequently, a series of different ligands for LP-CuNCs including thiolates, phosphines, alkynyl, polymers, and biomolecules are highlighted. Thereafter, their applications in different electrocatalytic reactions are discussed. It is believed that this review will not only inspire the design and synthesis of novel LP-CuNCs, but also contribute to the extension of their applications in electrocatalytic reactions and the establishment of accurate structure-performance relationships.     

Evaluation Model of Click Rate of Electronic Commerce Advertising Based on Fuzzy Genetic Algorithm

Mobile Networks and Applications - In order to improve the ability of quantitative evaluation of e-commerce advertising click rate, a model of e-commerce advertising click rate evaluation based on...     

Service placement strategy for joint network selection and resource scheduling in edge computing

The Journal of Supercomputing - In the edge computing, service placement refers to the process of installing service platforms, databases, and configuration files corresponding to computing tasks...     

A Survey on Long-Tailed Visual Recognition

The heavy reliance on data is one of the major reasons that currently limit the development of deep learning. Data quality directly dominates the effect of deep learning models, and the long-tailed distribution is one of the factors affecting data quality. The long-tailed phenomenon is prevalent due to the prevalence of power law in nature. In this case, the performance of deep learning models is often dominated by the head classes while the learning of the tail classes is severely underdeveloped. In order to learn adequately for all classes, many researchers have studied and preliminarily addressed the long-tailed problem. In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed studies. Specifically, we summarize these studies into ten categories from the perspective of representation learning, and outline the highlights and limitations of each category. Besides, we have studied four quantitative metrics for evaluating the imbalance, and suggest using the Gini coefficient to evaluate the long-tailedness of a dataset. Based on the Gini coefficient, we quantitatively study 20 widely-used and large-scale visual datasets proposed in the last decade, and find that the long-tailed phenomenon is widespread and has not been fully studied. Finally, we provide several future directions for the development of long-tailed learning to provide more ideas for readers.

     

From vasopressin receptor to water channel: intracellular traffic, constraint and by-pass

To test a potential "gating" effect of noradrenaline (NA) in the auditory cortex, the acoustic threshold was estimated by determining the rate-level function of neurons before, during, and after microiontophoretic application (5-40 nA) of NA. The rationale behind this experiment was that a gating effect should decrease the threshold for acoustic excitatory responses. From 84 recorded neurons, we observed (1) that application of NA increased the threshold for 48 of 84 cells, and (2) that, on average, the slope of the rate-level functions was unchanged. These effects on the threshold are consistent with the fact that the dominant effect of NA on the evoked response is inhibition for 34 of 84 cells; increases in evoked responses were observed for only 14 of 84 cells. GABA application (0-50 nA) also led to increased response threshold for 19 of 24 cells (unaffected, 5 of 24 cells). However, for three cells the effect of GABA application was antagonized by bicuculline application, while on the same cells bicuculline application did not prevent the noradrenergic increase in threshold. The effect induced by NA on the threshold raises questions about the generality of a gating effect of NA in sensory neocortex.     

Absorption effect in the calculation of a second-order nonlinear coefficient from the data of a maker fringe experiment

The effect of light absorption by sample in the analysis of Makerfringe data for estimating a second-order nonlinear coefficient hasbeen studied experimentally. Two theories, one by Jerphagnon andKurtz that neglects the absorption effect and one by Herman and Haydenthat takes into account the absorption effect, were compared with theexperimental results. It was found that Jerphagnon and Kurtz'sformula was unable to predict correctly not only the magnitude but alsothe incident angle dependence or the sample thickness dependence of thesecond harmonic signal generated by the sample with strong absorption, whereas the theory by Herman and Hayden was able to make thosepredictions fairly well. It was also found that the error in theestimated nonlinear coefficient when one uses Jerphagnon and Kurtz'sformula could be as large as 2-4 times the true value, depending onsample thickness.     

A study of a new data association and track initiation method with normalized distance squared ordering

In an underwater environment, measurements regarding true targets and false targets (clutter) can be made. Therefore, a suitable data association method to exactly detect and track a target and an efficient track initiation method for judging tracks formed by the target should be selected in this environment. This paper attempts to propose a new data association method and track initiation method to detect and track targets more effectively. Also, the performance of the new method is tested in a series of Monte Carlo simulation runs and is compared with the existing data association and track initiation methods in a cluttered environment.     

基于SOPC的RSA密码芯片设计

为了提高RSA密码算法在密码芯片上的实现性能,基于SOPC技术设计了一款RSA密码芯片,完成了NIOS Ⅱ的软硬件协同设计.该硬件系统由处理器、存储模块和自定义指令3部分组成,其关键的模乘模块采用改进的模乘算法和交叉存取设计方案设计实现,显著提高了系统性能.整体设计在ALTERA的CYCLONEⅡ器件上进行了验证与测试,并进行了逻辑综合及布局布线.与传统的RSA密码芯片设计相比,该芯片系统灵活性高,资源占用少.     

Dynamically modulated intensity interrogation scheme using waveguide coupled surface plasmon resonance sensors

An electro-optically modulated intensity interrogation method based on tunable waveguide coupled surface plasmon resonance sensors has been proposed. It has been theoretically and experimentally demonstrated that the proposed scheme can enable sensitive measurement of measurand variations. By modulating the refractive index in the waveguide layer, this interrogation method yields modulated signal whose amplitude is related to measurand's refractive index. This amplitude modulated signal offers a higher signal to noise ratio and eliminates additive noise in the sensor system. A preliminary investigation using saline buffers with different NaCl concentrations shows a resolution of 2.3 × 10^?6 refractive index unit by our approach. Resolution can be controlled by the amplitude of the applied modulation voltage and can be further enhanced by optimizing the device structure or improving the electro-optical (E-O) coefficient of the E-O material. This approach is simple, stable, and promising for low-cost or multi-channel SPR biosensor applications.