The Advantage of Low-Delta Electroencephalogram Phase Feature for Reconstructing the Center-Out Reaching Hand Movements

It is an emerging frontier of research on the use of neural signals for prosthesis control, in order to restore lost function to amputees and patients after spinal cord injury. Compared to the invasive neural signal based brain-machine interface (BMI), a non-invasive alternative, i.e., the electroencephalogram (EEG)-based BMI would be more widely accepted by the patients above. Ideally, a real-time continuous neuroprosthestic control is required for practical applications. However, conventional EEG-based BMIs mainly deal with the discrete brain activity classification. Until recently, the literature has reported several attempts for achieving the real-time continuous control by reconstructing the continuous movement parameters (e.g., speed, position, etc.) from the EEG recordings, and the low-frequency band EEG is consistently reported to encode the continuous motor control information. Previous studies with executed movement tasks have extensively relied on the amplitude representation of such slow oscillations of EEG signals for building models to decode kinematic parameters. Inspired by the recent successes of instantaneous phase of low-frequency invasive brain signals in the motor control and sensory processing domains, this study examines the extension of such a slow-oscillation phase representation to the reconstructing two-dimensional hand movements, with the non-invasive EEG signals for the first time. The data for analysis are collected on five healthy subjects performing 2D hand center-out reaching along four directions in two sessions. On representative channels over the cortices encoding the execution information of reaching movements, we show that the low-delta EEG phase representation is characterized by higher signal-to-noise ratio and stronger modulation by the movement tasks, compared to the low-delta EEG amplitude representation. Furthermore, we have tested the low-delta EEG phase representation with two commonly used linear decoding models. The results demonstrate that the low-delta EEG phase based decoders lead to superior performance for 2D executed movement reconstruction to its amplitude based counterparts, as well as the other-frequency band amplitude and power based features. Thus, our study contributes to improve the movement reconstruction from EEG by introducing a new feature set based on the low-delta EEG phase patterns, and demonstrates its potential for continuous fine motion control of neuroprostheses

Palladium Cobalt-nickel mixed oxides Surface modification Synergistic interaction Lean methane combustion

The effective transformation of lignin is an essential part of realizing the comprehensive utilization of biomass. In this study, a one-pot method for the depolymerization of corn stover lignin used aluminum phosphate (NiAPO-5) zeolite catalyst contained Brønsted acid, Lewis acid and hydrogenation sites was proposed. It was found that the number of Brønsted acid sites was increased after NiAPO-5 was reduced with H2. The yield of monomers and residue were 35.70% and 38.09% at 235 ◦C for 3 h, respectively. The result of 2D HSQC NMR showed that the NiAPO-5 (H2) catalyst significantly affected the cleavage of β-O-4 bonds. The distribution of products and the stability of catalyst revealed that NiAPO-5 (H2) was an efficient catalyst for the depolymerization of lignin

Proteomic analysis of elite soybean Jidou17 and its parents using iTRAQ-based quantitative approaches

BACKGROUND: Derived from Hobbit as the female parent and Zao5241 as the male parent, the elite soybean cultivar Jidou17 is significantly higher yielding and shows enhanced qualities and stronger resistance to non-biological stress than its parents. The purpose of this study is to understand the difference in protein expression patterns between Jidou17 and its parental strains and to evaluate the parental contributions to its elite traits. RESULTS: Leaves (14 days old) from Jidou17 and its parental cultivars were analysed for differential expressed proteins using an iTRAQ-based (isobaric tags for relative and absolute quantitation) method. A total of 1269 proteins was detected, with 141 and 181 proteins in Jidou17 differing from its female and male parent, respectively. Functional classification and an enrichment analysis based on biological functions, biological processes, and cellular components revealed that all the differential proteins fell into many functional categories but that the number of proteins varied greatly for the different categories, with enrichment in specific categories. A pathway analysis indicated that the differentiated proteins were mainly classified into the ribosome assembly pathway. Protein expression clustering results showed that the expression profiles between Jidou17 and its female parent Hobbit were more similar than those between Jidou17 and its male parent Zao5241 and between the two parental strains. Therefore, the female parent Hobbit contributed more to the Jidou17 genotype. CONCLUSIONS: This study applied a proven technique to study proteomics in 14-day-old soybean leaves and explored the depth and breadth of soybean protein research. The results provide new data for further understanding the mechanisms of elite cultivar development

Grip Force and 3D Push-Pull Force Estimation Based on sEMG and GRNN

The estimation of the grip force and the 3D push-pull force (push and pull force in the three dimension space) from the electromyogram (EMG) signal is of great importance in the dexterous control of the EMG prosthetic hand. In this paper, an action force estimation method which is based on the eight channels of the surface EMG (sEMG) and the Generalized Regression Neural Network (GRNN) is proposed to meet the requirements of the force control of the intelligent EMG prosthetic hand. Firstly, the experimental platform, the acquisition of the sEMG, the feature extraction of the sEMG and the construction of GRNN are described. Then, the multi-channels of the sEMG when the hand is moving are captured by the EMG sensors attached on eight different positions of the arm skin surface. Meanwhile, a grip force sensor and a three dimension force sensor are adopted to measure the output force of the human's hand. The characteristic matrix of the sEMG and the force signals are used to construct the GRNN. The mean absolute value and the root mean square of the estimation errors, the correlation coefficients between the actual force and the estimated force are employed to assess the accuracy of the estimation. Analysis of variance (ANOVA) is also employed to test the difference of the force estimation. The experiments are implemented to verify the effectiveness of the proposed estimation method and the results show that the output force of the human's hand can be correctly estimated by using sEMG and GRNN method

Genetic analysis of arabidopsis mutants impaired in plastid lipid import reveals a role of membrane lipids in chloroplast division

The biogenesis of photosynthetic membranes in plants relies largely on lipid import from the endoplasmic reticulum (ER) and this lipid transport process is mediated by TGD proteins in Arabidopsis. Such a dependency of chloroplast biogenesis on ER-to-plastid lipid transport was recently exemplified by analyzing double mutants between tgd1-1 or tgd4-3 and fad6 mutants. The fad6 mutants are defective in the desaturation of membrane lipids in chloroplasts and therefore dependent on import of polyunsaturated lipid precursors from the ER for constructing a competent thylakoid membrane system. In support of a critical role of TGD proteins in ER-to-plastid lipid trafficking, we showed that the introduction of the tgd mutations into fad6 mutant backgrounds led to drastic reductions in relative amounts of thylakoid lipids. Moreover, the tgd1-1 fad6 and tgd4-3 fad6 double mutants were deficient in polyunsaturated fatty acids in chloroplast membrane lipids, and severely compromised in the biogenesis of photosynthetic membrane systems. Here we report that these double mutants are severely impaired in chloroplast division. The possible role of membrane lipids in chloroplast division is discussed

The \u3ci\u3epgp1\u3c/i\u3e Mutant Locus of Arabidopsis Encodes a Phosphatidylglycerolphosphate Synthase with Impaired Activity

Phosphatidylglycerol is a ubiquitous phospholipid that is also present in the photosynthetic membranes of plants. Multiple independent lines of evidence suggest that this lipid plays a critical role for the proper function of photosynthetic membranes and cold acclimation. In eukaryotes, different subcellular compartments are competent for the biosynthesis of phosphatidylglycerol. Details on the plant-specific pathways in different organelles are scarce. Here, we describe a phosphatidylglycerol biosynthesis-deficient mutant of Arabidopsis, pgp1. The overall content of phosphatidylglycerol is reduced by 30%. This mutant carries a point mutation in the CDP-alcohol phosphotransferase motif of the phosphatidylglycerolphosphate synthase (EC 2.7.8.5) isoform encoded by a gene on chromosome 2. The mutant shows an 80% reduction in plastidic phosphatidylglycerolphosphate synthase activity consistent with the plastidic location of this particular isoform. Mutant plants are pale green, and their photosynthesis is impaired. This mutant provides a promising new tool to elucidate the biosynthesis and function of plastidic phosphatidylglycerol in seed plants

A Novel Sectionalizing Method for Power System Parallel Restoration Based on Minimum Spanning Tree

Parallel restoration is a way to accelerate the black-start procedure of power systems following a blackout. An efficient sectionalizing scheme can reduce the restoration time of a system, taking into account the black-start ability, generation-load balance of subsystems, restoration time of branches, start-up time of generating units, and effects of dispatchable loads and faulted devices. Solving the sectionalizing problem is challenging since it needs to handle a large number of Boolean variables corresponding to the branches and nonlinear constraints associated with system topology. This paper investigates power system sectionalizing problem for parallel restoration to minimize the system restoration time (SRT). A novel sectionalizing method considering the restoration of generating units and network branches is proposed. Firstly, the minimum spanning tree (MST) algorithm is used to determine the skeleton network of a power system. Secondly, the number of subsystems is determined according to the number of black-start units. Based on the skeleton network, candidate boundary lines among subsystems are identified. Then, constraints are evaluated to identify feasible sectionalizing schemes. Except commonly used constraints on power balancing and black-start units, this paper also considers using dispatchable loads to meet the minimum output requirements of generating units. Finally, the sectionalizing scheme with the minimum SRT is selected as the final solution. The effectiveness of the proposed method is validated by the IEEE 39-bus and 118-bus test systems. The simulation results indicate that the proposed method can balance the restoration time of subsystems and minimize the SRT