Three-dimensional higher-order raypath separation in a shallow-water waveguide.

Separating raypaths in a multipath shallow-water environment is a challenge due to the interferences between them and the colored noise that exists in an ocean environment, especially for two raypaths that arrive close to each other. Thus, in this paper, a three-dimensional (3D) higher-order raypath separation in an array to array configuration is proposed. Performance tests using simulation data in a multipath environment, real data obtained in an ultrasonic waveguide, and ocean shallow-water data, respectively, illustrate that the proposed algorithm achieves a higher resolution and a stronger robustness compared to the existing algorithms.

The flying spider-monkey tree fern genome provides insights into fern evolution and arborescence.

To date, little is known about the evolution of fern genomes, with only two small genomes published from the heterosporous Salviniales. Here we assembled the genome of Alsophila spinulosa, known as the flying spider-monkey tree fern, onto 69 pseudochromosomes. The remarkable preservation of synteny, despite resulting from an ancient whole-genome duplication over 100 million years ago, is unprecedented in plants and probably speaks to the uniqueness of tree ferns. Our detailed investigations into stem anatomy and lignin biosynthesis shed new light on the evolution of stem formation in tree ferns. We identified a phenolic compound, alsophilin, that is abundant in xylem, and we provided the molecular basis for its biosynthesis. Finally, analysis of demographic history revealed two genetic bottlenecks, resulting in rapid demographic declines of A. spinulosa. The A. spinulosa genome fills a crucial gap in the plant genomic landscape and helps elucidate many unique aspects of tree fern biology.

Unusual (2R,6R)-bicyclo[3.1.1]heptane ring construction in fungal α-trans-bergamotene biosynthesis.

Bergamotenes are bicyclo[3.1.1]heptane sesquiterpenes found abundantly in plants and fungi. Known bergamotene derivatives all possess (2S,6S)-bergamotene backbone. In this study, two (+)-α-trans-bergamotene derivatives (1 and 2) with unusual (2R,6R) configuration were isolated and elucidated from marine fungus Nectria sp. HLS206. The first (+)-α-trans-bergamotene synthase NsBERS was characterized using genome mining and heterologous expression-based strategies. Based on homology search, we characterized another (+)-α-trans-bergamotene synthase LsBERS from Lachnellula suecica and an (+)-α-bisabolol synthase BcBOS from Botrytis cinerea. We proposed that the cyclization mechanism of (+)-α-trans-bergamotene involved endo-anti cyclization of left-handed helix farnesyl pyrophosphate by (6R)-bisabolyl cation, which was supported by molecular docking. The biosynthesis-based volatiles (3-6) produced by heterologous fungal expression systems elicited significant electroantennographic responses of Helicoverpa armigera and Spodoptera frugiperda, respectively, suggesting their potential in biocontrol of these pests. This work enriches diversity of sesquiterpenoids and fungal sesquiterpene synthases, providing insight into the enzymatic mechanism of formation of enantiomeric sesquiterpenes.

[Advances in biosynthesis of cadinane sesquiterpenes].

Cadinanes are a class of bicyclic sesquiterpenes with complex stereochemistry and broad pharmacological activities, such as antibacterial, anti-inflammatory, and hypoglycemic activities. To date, structurally diverse and bioactive cadinane sesquiterpenes have been isolated and identified from a variety of plants and microorganisms. Moreover, deeper understandings on cadinane sesquiterpene synthases have been made. This article categorized the 124 new cadinanes which were published in the literatures in the past four years (2017-2020) into five structural types, and presented their pharmacological activities. We also illustrated the elucidation of the biosynthetic pathways for typical cadinanes, summarized the research progress on cadinane sesquiterpene synthases. Finally, current challenges and future prospects were proposed and discussed.

On the identification of the blood vessel confounding effect in intravoxel incoherent motion (IVIM) Diffusion-Weighted (DW)-MRI in liver: An efficient sparsity based algorithm.

IntraVoxel Incoherent Motion (IVIM) Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is of great interest for evaluating tissue diffusion and perfusion and producing parametric maps in clinical applications for liver pathologies. However, the presence of macroscopic blood vessels (not capillaries) in a given Region of Interest (ROI) results in a confounding effect that bias the quantification of tissue perfusion. Therefore, it is necessary to identify those voxels affected by blood vessels. In this paper, an efficient algorithm for an automatic identification of blood vessels in a given ROI is proposed. It relies on the sparsity of the spatial distribution of blood vessels. This sparsity prior can be easily incorporated using the all-voxel IVIM-MRI model introduced in this paper. In addition to the identification of blood vessels, the proposed algorithm provides a quantification of blood vessels, tissue diffusion and tissue perfusion of all voxels in a given ROI, in one single step. Besides, two strategies are proposed in this paper to deal with the nonnegativity of the model parameters. The efficiency of the proposed algorithm compared to the Non-Negative Least Square (NNLS)-based method, recently introduced to deal with the confounding blood vessel effect in the IVIM-MRI model, is confirmed using both realistic and real DW-MR images.

[Research on effective connectivity of intracerebral electroencephalogram based on Wiener-Granger Causality Index modified by generalized Akaike's Information Criterion].

The objective is to deal with brain effective connectivity among epilepsy electroencephalogram (EEG) signals recorded by use of depth electrodes in the cerebral cortex of patients suffering from refractory epilepsy during their epileptic seizures. The Wiener-Granger Causality Index (WGCI) is a well-known effective measure that can be useful to detect causal relations of interdependence in these kinds of EEG signals. It is based on the linear autoregressive model, and the issue of the estimation of the model parameters plays an important role in the calculation accuracy and robustness of WGCI to do research on brain effective connectivity. Focusing on this issue, a modified Akaike's information criterion algorithm is introduced in the computation of the WGCI to estimate the orders involved in the underlying models and in order to advance the performance of WGCI to detect brain effective connectivity. Experimental results support the interesting performance of the proposed algorithm to characterize the information flow both in a linear stochastic system and a physiology-based model.

Fast raypath separation based on low-rank matrix approximation in a shallow-water waveguide.

Subspace algorithms based on higher-order cumulants were developed to achieve high-resolution separation in non-Gaussian processes. However, singular value decomposition (SVD) of a huge matrix is an unavoidable step of these algorithms. The memory space and running time required by the decomposition are super-linear with respect to the size of the matrix, which is prohibitive in terms of practical applications. Thus, in this paper, a fast raypath separation algorithm based on low-rank matrix approximation is proposed in a shallow-water waveguide. The experimental results illustrate that the proposed algorithm dramatically reduces the consumption of time and space, with arbitrarily small error, compared to conventional higher-order cumulant-based algorithms.

Two-dimensional active raypath separation using examination of the roots of the spectrum polynomial.

The application of the root multiple signal classification algorithm for raypath separation was motivated by the dramatic reduction in processing time of the multiple-signal classification algorithm. However, the algorithm provides classification only in the direction of the arrival domain and fails to separate raypaths arriving at the array with similar directions of arrival. Moreover, for many applications in shallow water (such as ocean acoustic tomography and active sonar), the emitted signal is known and can be used as a priori information to improve the resolution. Thus, in this study, a two-dimensional active wideband classification algorithm is developed using the examination of the roots of the spectrum polynomial in the angle versus time domain. A two-step strategy is developed to enable extension to the two-dimensional case. The results of simulations confirm that the proposed algorithm achieves almost identical resolution as the existing two-dimensional algorithms while offering a significant reduction in computation time.

Active wideband higher-order raypath separation in multipath environment.

Multiple raypaths propagation is caused by reflection and refraction at the surface and the bottom of the water column. In this study, an active wideband higher-order separation is proposed, which enables the separation of raypaths interrupted by colored noise (as traditionally found in ocean environments) in the angle-vs-time domain. A comparative study shows that the proposed algorithm achieves a more accurate separation than other algorithms. Moreover, with the proposed approach, it is not necessary to assume that the number of sensors is larger than that of the sources. Furthermore, numerical results validate the noise suppression property of the proposed method.