catena-Poly[[[aqua­[(2-hydroxy­phen­yl)acetato-κ2 O,O′]lead(II)]-μ3-[(2-hydroxy­phen­yl)acetato-κ4 O:O,O′:O′]] monohydrate]

In the title complex, {[Pb(C8H7O3)2(H2O)]·H2O}n, the PbII atom is seven-coordinated by six carboxyl­ate O atoms from four different 2-hydroxy­phenyl­acetate (2-dph) ligands and one water mol­ecule, displaying a hemidirected irregular geometry, with the empty side of the metal ion capped by a benzene ring forming a Pb⋯π contact [Pb⋯centroid distance = 3.342 (2) Å]. One 2-dph ligand functions in a bridging mode and connects Pb ions into a linear chain. The crystal packing is governed by intra- and inter­molecular O—H⋯O hydrogen bonds

TVIR: a comprehensive vegetable information resource database for comparative and functional genomic studies

Vegetables are an indispensable part of the daily diet of humans. Therefore, it is vital to systematically study the genomic data of vegetables and build a platform for data sharing and analysis. In this study, a comprehensive platform for vegetables with a user-friendly Web interface—The Vegetable Information Resource (TVIR, http://tvir.bio2db.com)—was built based on the genomes of 59 vegetables. TVIR database contains numerous important functional genes, including 5215 auxin genes, 2437 anthocyanin genes, 15 002 flowering genes, 79 830 resistance genes, and 2639 glucosinolate genes of 59 vegetables. In addition, 2597 N6-methyladenosine (m6A) genes were identified, including 513 writers, 1058 erasers, and 1026 readers. A total of 2 101 501 specific clustered regularly interspaced short palindromic repeat (CRISPR) guide sequences and 17 377 miRNAs were detected and deposited in TVIR database. Information on gene synteny, duplication, and orthologs is also provided for 59 vegetable species. TVIR database contains 2 346 850 gene annotations by the Swiss-Prot, TrEMBL, Gene Ontology (GO), Pfam, and Non-redundant (Nr) databases. Synteny, Primer Design, Blast, and JBrowse tools are provided to facilitate users in conducting comparative genomic analyses. This is the first large-scale collection of vegetable genomic data and bioinformatic analysis. All genome and gene sequences, annotations, and bioinformatic results can be easily downloaded from TVIR. Furthermore, transcriptome data of 98 vegetables have been collected and collated, and can be searched by species, tissues, or different growth stages. TVIR is expected to become a key hub for vegetable research globally. The database will be updated with newly assembled vegetable genomes and comparative genomic studies in the future

3D Beamforming Based on Deep Learning for Secure Communication in 5G and beyond Wireless Networks

Three-dimensional (3D) beamforming is a potential technique to enhance communication security of new generation networks such as 5G and beyond. However, it is difficult to achieve optimal beamforming due to the challenges of nonconvex optimization problem and imperfect channel state information (CSI). To tackle this problem, this paper proposes a novel deep learning-based 3D beamforming scheme, where a deep neural network (DNN) is trained to optimize the beamforming design for wireless signals in order to guard against eavesdropper under the imperfect CSI. With our approach, the system is capable of training the DNN model offline, and the trained model can then be adopted to instantaneously select the 3D secure beamforming matrix for achieving the maximum secrecy rate of the system, which is measured by the signal received by eavesdroppers outside the path of the beam. Simulation results demonstrate that the proposed solution outperforms the classical deep learning algorithm and 2D beamforming solution in terms of the secrecy rate and robust performance.This research is supported by the National Research Foundation, Singapore under its Strategic Capability Research Centres Funding Initiative, Nanyang Technological University (NTU) Startup Grant, and SUTD SRG-ISTD-2021-165