Performance improvement of the LM device and its application to precise measurement of motion trajectories within a small range with a machining centre

In order to apply the LM device previously developed to precisely measuring small motion trajectories located on the different motion planes, three major improvements are successfully performed under the condition of completely maintaining the advantages of the device. These improvements include 1) development of a novel connection mechanism to smoothly attach the device to the spindle of a machining centre; 2) employment of a new data sampling method to achieve a high sampling frequency independent of the operating system of the control computer; and 3) proposal of a set-up method to conveniently install the device on the test machining centre with respect to different motion planes. Practical measurement experiment results with the improved device on a machining centre sufficiently demonstrate the effectiveness of the improvements and confirm several features including a very good response to small displacement close to the resolution of the device, high precision, repeatability and reliance. Moreover, based on the measurement results for a number of trajectories for a wide range of motion conditions, the error characteristics of small size motions are systematically discussed and the effect of the movement size and feed rate on the motion accuracy is verified for the machining centre tested

A sparse Bayesian learning method for structural equation model-based gene regulatory network inference

Gene regulatory networks (GRNs) are underlying networks identified by interactive relationships between genes. Reconstructing GRNs from massive genetic data is important for understanding gene functions and biological mechanism, and can provide effective service for medical treatment and genetic research. A series of artificial intelligence based methods have been proposed to infer GRNs from both gene expression data and genetic perturbations. The accuracy of such algorithms can be better than those models that just consider gene expression data. A structural equation model (SEM), which provides a systematic framework integrating both types of gene data conveniently, is a commonly used model for GRN inference. Considering the sparsity of GRNs, in this paper, we develop a novel sparse Bayesian inference algorithm based on Normal-Equation-Gamma (NEG) type hierarchical prior (BaNEG) to infer GRNs modeled with SEMs more accurately. First, we reparameterize an SEM as a linear type model by integrating the endogenous and exogenous variables; Then, a Bayesian adaptive lasso with a three-level NEG prior is applied to deduce the corresponding posterior mode and estimate the parameters. Simulations on synthetic data are run to compare the performance of BaNEG to some state-of-the-art algorithms, the results demonstrate that the proposed algorithm visibly outperforms the others. What’s more, BaNEG is applied to infer underlying GRNs from a real data set composed of 47 yeast genes from Saccharomyces cerevisiae to discover potential relationships between genes

Well wall water leakage control technology of vertical well drilling method in coal mines based on grouting of ground directional drilling

The coal mine drilling shaft wall is a single-layer structure, and water leakage in the deep alluvium will seriously threaten mine safety. If there are construction defects in the stubble part of the well wall at the construction stage, it will lead to groundwater corrosion and rust through the metal and the weld seam of the stubble part, resulting in water leakage from well wall, which, if not treated promptly, is prone to lead to a sudden water-sand inrush and flooding accidents. In order to explore an effective treatment technology, a research on the control technology of water leakage from the wall of coal mine drilling wells was carried out with the background of water leakage control of wall of sub-well of the Xutong Coal Mine. Firstly, the causes of water leakage from the single-layer well wall of the drilling method were analyzed with the information of hydrogeological characteristics of mine. It was found that the main reason of water leakage at the sub-well wall of Xutong Mine was that the high-pressure groundwater recharged from the aquifers flowed into the well through the gravel packing layer with great pore connectivity, after the corrosive effects of groundwater jointly penetrated the stubs of well walls. Then, the feasibility and safety of using post-wall grouting and ground drilling grouting for water leakage control in the wall of sub-well wall in Xutong Coal Mine were compared and analyzed. Post-wall grouting of reinforced concrete single-layer well walls constructed using the drilling method in fluvial sand layer was found to pose a high safety risk, affecting the normal lifting of wellbore and risking the reoccurrence of water leakage. Ground directional drilling grouting technology had a large grouting volume, and the pores in the gravel filling layer behind the wall can be fully filled by cement slurry, improving the leakage prevention and bearing capacity of the wellbore, and the construction personnel operated on the ground, which was safe and did not affect the normal lifting of the wellbore. Finally, the ground directional drilling grouting technology for water leakage control of coal mine wall in deep alluvium was proposed and demonstrated. A total of 130.9 m3 of cement slurry was injected into the two boreholes, which completely filled the pores space between the gravel of the filling layer behind the wall of the layer from 94.00-131.40 m, and successfully blocked the water outlet point at 94 m downhole. No further water leakage from this section of the well wall had been observed on site over a long period of time. The research results shown that, the ground directional drilling grouting technology had good control effect and high safety for the water leakage of coal mine drilling well wall in deep alluvium. The research results can provide a certain reference for the water leakage control of coal mine drilling well wall in deep alluvium

Data acquisition system for in situ monitoring of chemoelectrical potential in living plant fuel cells

Photosynthesis process in plants generates numerous sources of bioenergy. However, only a small fraction is readily exploited for electrical energy. The impact of environmental factors is one of the significant physiological influences on the electrical potential of the plants. Hence, we developed a data acquisition (DAQ) system for instantaneous monitoring of electrical potential in plants and Aloe vera was used as a plant sample. The static response characterization, capability index (P/T), and Pearson’s coefficient of correlation procedures were applied to assess the reliability of the obtained data. This developed system offers the capability of in situ monitoring and detecting gradual changes in the electrical potential of plants up to a correlational strength of greater than 0.7. Interpretation of the electrical signal mechanisms in the Aloe vera plant and the optimization of the electricity can be achieved through the application of this monitoring system. This system, therefore, can serve as a tool to measure and analyze the electrical signals in plants at different conditions

Mitochondrial genome diversity in Beta vulgaris L. ssp. vulgaris (Leaf and Garden Beet Groups) and its implications concerning the dissemination of the crop

Four mitochondrial minisatellites were used to study cytoplasmic diversity in leaf and garden beet germplasm resources. Eleven multi-locus haplotypes were identified, of which one (named mitochondrial minisatellite haplotype 4, hereafter min04) was associated with male-sterile Owen cytoplasm and two others (min09 and min18), with a normal fertile cytoplasm. European leaf beet germplasm exhibited the greatest haplotype diversity, with min09 and min18 predominating. In North African leaf beet accessions, only these two haplotypes were observed, making it likely that North African accessions were descended from European genotypes. The prevalence of min18 was also noted in leaf beet from the Middle East and western Asia. Such a pattern contrasts with that found in east Asian leaf beet where the two haplotypes were extremely rare. The geographical structure of the mitochondrial haplotypes allowed us to infer possible dissemination pathways of leaf beet. Additionally, we showed that mitochondrial genome diversity was low in garden beet germplasm, with min18 being highly predominant. An explanation of this limited diversity may lie in the geographically restricted origin of as well as relatively short cultivation histories of garden beet

Identification of the Genes Encoding B3 Domain-Containing Proteins Related to Vernalization of Beta vulgaris

Vernalization is the process of exposure to low temperatures, which is crucial for the transition from vegetative to reproductive growth of plants. In this study, the global landscape vernalization-related mRNAs and long noncoding RNAs (lncRNAs) were identified in Beta vulgaris. A total of 22,159 differentially expressed mRNAs and 4418 differentially expressed lncRNAs were uncovered between the vernalized and nonvernalized samples. Various regulatory proteins, such as zinc finger CCCH domain-containing proteins, F-box proteins, flowering-time-related proteins FY and FPA, PHD finger protein EHD3 and B3 domain proteins were identified. Intriguingly, a novel vernalization-related lncRNA–mRNA target-gene co-expression regulatory network and the candidate vernalization genes, VRN1, VRN1-like, VAL1 and VAL2, encoding B3 domain-containing proteins were also unveiled. The results of this study pave the way for further illumination of the molecular mechanisms underlying the vernalization of B. vulgaris

Whole-Transcriptome RNA Sequencing Reveals the Global Molecular Responses and CeRNA Regulatory Network of mRNAs, lncRNAs, miRNAs and circRNAs in Response to Salt Stress in Sugar Beet (Beta vulgaris)

Sugar beet is an important sugar-yielding crop with some tolerance to salt, but the mechanistic basis of this tolerance is not known. In the present study, we have used whole-transcriptome RNA-seq and degradome sequencing in response to salt stress to uncover differentially expressed (DE) mRNAs, microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in both leaves and roots. A competitive endogenous RNA (ceRNA) network was constructed with the predicted DE pairs, which revealed regulatory roles under salt stress. A functional analysis suggests that ceRNAs are implicated in copper redistribution, plasma membrane permeability, glycometabolism and energy metabolism, NAC transcription factor and the phosphoinositol signaling system. Overall, we conducted for the first time a full transcriptomic analysis of sugar beet under salt stress that involves a potential ceRNA network, thus providing a basis to study the potential functions of lncRNAs/circRNAs

The Memory of Rice Response to Spaceflight Stress: From the Perspective of Metabolomics and Proteomics

The stress response of plants to spaceflight has been confirmed in contemporary plants, and plants retained the memory of spaceflight through methylation reaction. However, how the progeny plants adapt to this cross-generational stress memory was rarely reported. Here, we used the ShiJian-10 retractable satellite carrying Dongnong416 rice seeds for a 12.5-day on-orbit flight and planted the F2 generation after returning to the ground. We evaluated the agronomic traits of the F2 generation plants and found that the F2 generation plants had no significant differences in plant height and number of tillers. Next, the redox state in F2 plants was evaluated, and it was found that the spaceflight broke the redox state of the F2 generation rice. In order to further illustrate the stress response caused by this redox state imbalance, we conducted proteomics and metabolomics analysis. Proteomics results showed that the redox process in F2 rice interacts with signal transduction, stress response, and other pathways, causing genome instability in the plant, leading to transcription, post-transcriptional modification, protein synthesis, protein modification, and degradation processes were suppressed. The metabolomics results showed that the metabolism of the F2 generation plants was reshaped. These metabolic pathways mainly included amino acid metabolism, sugar metabolism, cofactor and vitamin metabolism, purine metabolism, phenylpropane biosynthesis, and flavonoid metabolism. These metabolic pathways constituted a new metabolic network. This study confirmed that spaceflight affected the metabolic changes in offspring rice, which would help better understand the adaptation mechanism of plants to the space environment

Quantitative Structure–Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I‑Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure–activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography–tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC₅₀ was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC₅₀ = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides