Applications of Molecular Spectroscopic Methods to the Elucidation of Lignin Structure

Lignin in plant cell wall is a complex amorphous polymer and is biosynthesized mainly from three aromatic alcohols, namely, p-coumaryl, coniferyl, and sinapyl alcohols. This biosynthesis process consists of mainly radical coupling reactions and creates a unique lignin polymer in each plant species. Generally, lignin mainly consists of p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S) units and is linked by several types of carbon-carbon (β-β, β-5, β-1, and 5–5) and ether bonds. Due to the structural complexity, various molecular spectroscopic methods have been applied to unravel the aromatic units and different interunit linkages in lignin from different plant species. This chapter is focused on the application of ultraviolet (UV) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, Fourier transform Raman (FT-Raman) spectroscopy, fluorescence spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy to lignin structural elucidation

Improved SVD + + Recommendation Algorithm Based on Fusion Time Factor

Collaborative filtering algorithm is widely used in recommendation system. Aiming at the problems of data sparsity and low recommendation accuracy in traditional collaborative filtering algorithm, an improved recommendation algorithm is proposed PT _ SVD++. Firstly, the attribute information of users and the implicit feedback information of items are introduced to improve the SVD++ algorithm, which solves the insufficient utilization of information and alleviates the problem of sparse data；Secondly the time effect model is established to further improve the accuracy of the prediction results. The experimental results on MovieLens dataset show that compared with other algorithms, the average absolute error and root mean square error of this algorithm are lower, and its recommendation accuracy is higher

Multi-level anomaly detection in industrial control systems via package signatures and LSTM networks

We outline an anomaly detection method for industrial control systems (ICS) that combines the analysis of network package contents that are transacted between ICS nodes and their time-series structure. Specifically, we take advantage of the predictable and regular nature of communication patterns that exist between so-called field devices in ICS networks. By observing a system for a period of time without the presence of anomalies we develop a base-line signature database for general packages. A Bloom filter is used to store the signature database which is then used for package content level anomaly detection. Furthermore, we approach time-series anomaly detection by proposing a stacked Long Short Term Memory (LSTM) network-based softmax classifier which learns to predict the most likely package signatures that are likely to occur given previously seen package traffic. Finally, by the inspection of a real dataset created from a gas pipeline SCADA system, we show that an anomaly detection scheme combining both approaches can achieve higher performance compared to various current state-of-the-art techniques

Sum-frequency generation from etchless lithium niobate empowered by dual quasi-bound states in the continuum

The miniaturization of nonlinear light sources is central to the integrated photonic platform, driving a quest for high-efficiency frequency generation and mixing at the nanoscale. In this quest, the high-quality ($Q$) resonant dielectric nanostructures hold great promise, as they enhance nonlinear effects through the resonantly local electromagnetic fields overlapping the chosen nonlinear materials. Here, we propose a method for the enhanced sum-frequency generation (SFG) from etcheless lithium niobate (LiNbO$_{3}$) by utilizing the dual quasi-bound states in the continuum (quasi-BICs) in a one-dimensional resonant grating waveguide structure. Two high-$Q$ guided mode resonances corresponding to the dual quasi-BICs are respectively excited by two near-infrared input beams, generating a strong visible SFG signal with a remarkably high conversion efficiency of $3.66\times10^{-2}$ (which is five orders of magnitude higher than that of LiNbO$_{3}$ films of the same thickness) and a small full-width at half-maximum less than 0.2 nm. The SFG efficiency can be tuned via adjusting the grating geometry parameter or choosing the input beam polarization combination. Furthermore, the generated SFG signal can be maintained at a fixed wavelength without the appreciable loss of efficiency by selectively exciting the angular-dependent quasi-BICs, even if the wavelengths of input beams are tuned within a broad spectral range. Our results provide a simple but robust paradigm of high-efficiency frequency conversion on an easy-fabricated platform, which may find applications in nonlinear light sources and quantum photonics

High-efficient optical frequency mixing in all-dielectric metasurface empowered by multiple bound states in the continuum

We present nonlinear optical four-wave mixing in a silicon nanodisk dimer metasurface. Under the oblique incident plane waves, the designed metasurface exhibits a multi-resonant feature with simultaneous excitations of three quasi-bound states in the continuum (BIC). Through employing these quasi-BIC with maximizing electric field energy at the input bump wavelengths, significant enhancements of third-order nonlinear processes including third-harmonic generation, degenerate and non-degenerate four-wave mixing are demonstrated, giving rise to ten new frequencies in the visible wavelengths. This work may lead to a new frontier of ultracompact optical mixer for applications in optical circuitry, ultrasensitive sensing, and quantum nanophotonics