Chromosome-level genome assembly of the king horseshoe bat (Rhinolophus rex) provides insights into its conservation status and chromosomal evolution of Rhinolophus.

A high-quality reference genome is quite valuable in assessing the conservation status of a rare species when adequate data from other sources are unavailable. Bats comprise almost a fifth of all mammals and contribute greatly to ecosystem. However, due to the nocturnal and elusive habits, it is difficult to obtain the accurate census population size of a rare bat species and assess its conservation status.

Chromosome-level genome assembly of the Stoliczka's Asian trident bat (Aselliscus stoliczkanus).

Stoliczka's Asian trident bat (Aselliscus stoliczkanus) is a small-bodied species and very sensitive to climate change. Here, we presented a chromosome-level genome assembly of A. stoliczkanus by combining Illumina sequencing, Nanopore sequencing and high-throughput chromatin conformation capture (Hi-C) sequencing technology.

Rapid degradation of malachite green by CoFeO-SiC foam under microwave radiation.

This study demonstrated rapid degradation of malachite green (MG) by a microwave (MW)-induced enhanced catalytic process with CoFeO-SiC foam. The catalyst was synthesized from CoFeO particles and SiC foam by the hydrothermal method. X-ray diffraction and scanning electron microscopy techniques were used to confirm that CoFeO particles were settled on the surface of SiC foam.

Theoretical and experimental study of the mechanisms of phosphate removal in the system containing Fe(III)-ions.

A process-oriented investigation of phosphate removal by ferric salt was carried out in this study. The kinetics of amorphous ferric phosphate (FePO(s)) formation has been investigated over the pH range of 6.0-8.

An effective hybrid approach of gene selection and classification for microarray data based on clustering and particle swarm optimization.

In this paper, a hybrid approach based on clustering and Particle Swarm Optimisation (PSO) is proposed to perform gene selection and classification for microarray data. In the new method, firstly, genes are partitioned into a predetermined number of clusters by K-means method. Since the genes in each cluster have much redundancy, Max-Relevance Min-Redundancy (mRMR) strategy is used to reduce redundancy of the clustered genes.