Transcriptome provides potential insights into how calcium affects the formation of stone cell in Pyrus.

Background: The content of stone cells in pears has a great influence on taste. Stone cells are formed by the accumulation of lignin. The treatment of exogenous calcium can affect the lignin synthesis, but this Ca-mediated mechanism is still unclear.

Analysis of Gene Family and Its Function on Cell Lignification in Pears ().

Class III peroxidases (PRXs) are plant-specific enzymes that play key roles in the responses to biotic and abiotic stress during plant growth and development. In addition, some peroxidases also play roles in plant lignification. In this study, a total of 114 (designated ) genes were identified in the pear () genome based on systematic analysis.

Genes: Genome-Wide Identification, Evolution, and Their Contribution to Lignin Biosynthesis in Pear ().

The synthetic enzyme cinnamyl alcohol dehydrogenase (CAD) is involved in responses to various stresses during plant growth. It regulates the monolignol biosynthesis and catalyzes hydroxyl cinnamaldehyde reduction to the corresponding alcohols. Although the CAD gene families have been explored in some species, little known is in Rosaceae.

Multi-Sensor Perception Strategy to Enhance Autonomy of Robotic Operation for Uncertain Peg-in-Hole Task.

The peg-in-hole task with object feature uncertain is a typical case of robotic operation in the real-world unstructured environment. It is nontrivial to realize object perception and operational decisions autonomously, under the usual visual occlusion and real-time constraints of such tasks. In this paper, a Bayesian networks-based strategy is presented in order to seamlessly combine multiple heterogeneous senses data like humans.

regulates lignification during stone cell development in pear () fruit.

Programmed cell death (PCD) and secondary cell wall (SCW) thickening in pear fruit are accompanied by the deposition of cellulose and lignin to form stone cells. Metacaspase is an important protease for development, tissue renewal and PCD. The understanding of the molecular mechanism whereby pear () metacaspase promotes PCD and cell wall lignification is still limited.

A Mobile Anchor Node Assisted RSSI Localization Scheme in Underwater Wireless Sensor Networks.

In this paper, a mobile anchor node assisted RSSI localization scheme in underwater wireless sensor networks (UWSNs) is proposed, which aims to improve location accuracy and shorten location time. First, to improve location accuracy, we design a support vector regression (SVR) based interpolation method to estimate the projection of sensor nodes on the linear trajectory of the mobile anchor node. The proposed method increases the accuracy of the nonlinear regression model of noisy measured data and synchronously decreases the estimation error caused by the discreteness of measured data.

Combining pseudo dinucleotide composition with the Z curve method to improve the accuracy of predicting DNA elements: a case study in recombination spots.

Pseudo dinucleotide composition (PseDNC) and Z curve showed excellent performance in the classification issues of nucleotide sequences in bioinformatics. Inspired by the principle of Z curve theory, we improved PseDNC to give the phase-specific PseDNC (psPseDNC). In this study, we used the prediction of recombination spots as a case to illustrate the capability of psPseDNC and also PseDNC fused with Z curve theory based on a novel machine learning method named large margin distribution machine (LDM).

An energy-efficient underground localization system based on heterogeneous wireless networks.

A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations.

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.