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During the loading operation of a ship loader in bulk terminal, in order to bring bulk cargo, such as coal and ore, precisely into every corner of the cabin and not to raise dust at the same time, the slip barrel mechanism usually is placed fully inside the ship cabin near the cargo as close as possible. However, if too close, it will increase the risk of collision between slip barrel and cargo, which poses a security risk to loading operation. This article proposes an anti-collision method for slip barrel in the process of automatic ship loading in bulk terminal. This method can accurately position the cargo of cabin which is blocked by slip barrel and shovel, and provide a reliable guarantee for the automatic loading operation. Firstly, this method use an array of laser radar mounted on the maintenance platforms to perceive the collision objects around the slip barrel, including the cargo and cabin. Meanwhile, it provides a compensation algorithm to reduce the effect of anti-collision recognition brought by dust and various obstacles during the operation. According to the calculated effective distance between the cargo and slip barrel, the automatic control system of ship loading can adjust the loading operation on a real-time basis. In the end, this article analyze and illustrate the reliability and validity of this method by the case of the application in automatic ship loading system in Tianjin coal terminal
Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem
This article proposes a method of locating and recognizing lockholes in shipping container corner castings. This method converts the original image of the containers captured by a camera into the HSV (Hue, Saturation, Value) color space. To reduce the influence of the surface color of the containers and lights from the environment on the locating and recognizing algorithm, most noisy points of the image are filtered by binarization and a morphology opening operation to make the features of the containers clearer in the image. Thus, the container body can be separated from the total image. Then, the position and size of the corner castings are defined through calculation based on the international standard of the shipping container size. Lastly, by using this method, we can locate the corner casting in the image by using the General Hough Transform fitting algorithm onto ellipses
Stowage planning is the core of ship planning. It directly influences the seaworthiness of container ship and the handling efficiency of container terminal. As the latter step of container ship stowage plan, terminal stowage planning optimizes terminal cost according to pre-plan. Group-Bay stowage planning is the smallest sub problem of terminal stowage planning problem. A group-bay stowage planning model is formulated to minimize relocation, crane movement and target weight gap satisfying both ship owner and container terminal. A GA-A* hybrid algorithm is designed to solve this problem. Numerical experiment shown the validity and the efficiency
Selenium (Se) is indispensable to animals. The aims of this study were to explore the threshold dose of Se application in soil and reveal the mechanism of selenite effect on alfalfa growth, which is important for producing Se-enriched forage. Pot experiments were carried out in a greenhouse to explore the physiological mechanisms that are related to the response of forage crop to Se application. Alfalfa plants were treated with different Se levels (Se as Na₂SeO₃ dissolved in water was evenly sprinkled on the soil) to determine the effects of selenite supply on antioxidant activity, photosynthetic parameters, root activities, and the absorption of essential elements of alfalfa. Compared with the control plants, those treated with 5 and 10 mg kg⁻¹ Se exhibited increased shoot Se concentrations by 4.5- and 8.1-fold, respectively. The Se partitioning factors for alfalfa ranged from 0.47 to 0.89. The dry weights of roots and whole plants reached maximum values after applying 1 mg kg⁻¹ Se. At < 20 mg kg⁻¹ Se, plant growth was not inhibited in contrast to the control plants, and the activities of antioxidants superoxide dismutase (SOD), peroxidase (POD), and glutathione peroxidase (GSH-Px) increased, whereas the MDA content decreased significantly. With low-dose Se, the photosynthetic parameters (except for intercellular CO₂ concentration), leaf pigment content, and root activities were significantly enhanced, and the absorption of micronutrient elements (Fe and Mn) was promoted. However, at > 20 mg kg⁻¹ Se, the plant growth, antioxidant enzyme activity, photosynthetic parameters, root activity, and P and K absorption were inhibited. Alfalfa growth was not negatively affected by Se application less than 20 mg kg⁻¹. Low-dose selenite (0.5 and 1 mg kg⁻¹ Se) stimulated plant growth, mainly due to the stimulation of root growth by enhancing root activities and therefore promoting the absorption of P, K, Ca, Fe, and Mn. The increase in antioxidant enzyme activity and net photosynthetic rate partially resulted from the increased carotenoid content, which also contributed to the increasing dry matter at low-dose selenite levels. Given the relatively high transport efficiency of Se from root to overground part, alfalfa can be potentially used in the production of Se-enriched forage, and 10 mg kg⁻¹ Se is the optimum reference dose of Se application in soil.
Drought is one of the main limiting factors for peanut yield worldwide. However, the underlying genetic and molecular mechanisms remain unclear. In this study, we identified several water deficiency tolerant peanut germplasms based on physiological properties in the seedling stage. One of the germplasms was further characterized by transcriptome sequencing of samples that had been untreated or treated with PEG 6000 at three different times. A total of 370,145 non-redundant transcripts and 141,289 unigenes were obtained, and differentially expressed transcripts were identified among samples. Based on functional annotation, transcripts involved in drought response pathways were selected for qPCR analysis. Similar patterns but different levels of gene expression were found between drought-tolerant and drought-sensitive germplasms. These findings provide useful insights into drought tolerance of peanut.
A full-length cDNA, SmPR10-1, encoding a pathogenesis-related class 10 protein, was isolated from Salvia miltiorrhiza, a well-known Chinese herbal plant. From the coding region of nucleotide sequence, the amino acid sequence can be predicted which contained conserved domain (K–A–X–E–X–Y) in the C-terminal helix found in most members of the PR10 protein family. Phylogenetic tree analysis indicated that the SmPR10-1 protein showed a sequence similarity which was much higher to dicot proteins than to other PR10 proteins. Prokaryotic expression of SmPR10-1 protein in fusion with a His-tag produced a 22 kDa protein in E. coli BL21 (DE3), which exhibited ribonuclease activity in vitro. The purified protein was used to assay antifungal activity and the results showed SmPR10-1 only inhibited the growth of Phytophthora infestans. The RT-PCR results showed that the SmPR10-1 was expressed in high transcript level in leaves, stalks and low levels in roots. This protein seems to involve in the plant active defense response through activation of the methyl jasmonate signaling pathway rather than salicylic acid or abscisic acid pathway.
Dysosma versipellis (Hance) M. Cheng is an endangered plant due to overharvesting for the extraction of podophyllotoxin. Thus, the in vitro technique is valuable for the propagation of this species. When the explants of rhizome buds were cultured on Murashige and Skoog’s (MS) medium with 6-benzyladenine (BA) (1.0 mg l⁻¹), gibberellic acid (GA₃) (0.5 mg l⁻¹) and zeatin (Zea) (0.5 mg l⁻¹), multiple buds were regenerated directly on the explants without callusing within 6 weeks. Callus was induced from the leaf segment cultures on MS basal medium supplemented with 2,4-dichlorophenoxyacetic acid (2,4-D) (0.5 mg l⁻¹) and BA (0.2 mg l⁻¹) within 4 weeks. The adventitious buds were differentiated when the calli were subcultured on MS medium supplemented with BA (1.0 mg l⁻¹) and thidiazuron (TDZ) (0.2 mg l⁻¹) within 6 weeks. The adventitious buds obtained from callus and the rhizome-buds rooted with a frequency of 100% on half strength MS medium fortified with indole-3-butyric acid (IBA) 0.5 mg l⁻¹ and activated charcoal (AC) 0.5 g l⁻¹ for 4 weeks. The rooted shoots were successfully transplanted from a mixture of vermiculite:soil (1:1 v/v) to the field with a survival rate of 85%. Podophyllotoxin production in calli, cultured rhizomes, rhizomes of transplanting plants from the garden and rhizomes in the wild field was confirmed by high-performance liquid chromatography (HPLC) analysis. Our results suggest that calli, cultured rhizomes and rhizomes of transplanting plants would be the potential sources of podophyllotoxin.
We collected and analyzed atmospheric particulates in Changji, China, in order to investigate size distribution of atmospheric particulates and Pb concentrations in TSP during cold-weather heating periods. The results indicated that during such periods, contamination increased as particle size decreased. As compared with the non-heating period, the concentrations of atmospheric particulates were relatively higher during the heating period. The concentrations of TSP, PM10, PM5, and PM2.5 had two peaks during this time. Coal combustion and meteorological variables – especially temperature – could be the main contributing factors. The size distribution of atmospheric particulates had certain regularity. The ratio of atmospheric particulates with size under 2.5 μm in TSP first increased and then decreased during the heating period. Atmospheric particulates with size between 2.5 to 5, 5 to 10, and 10 to 100 μm in TSP had the same change trend of first decreasing and then increasing. The change in the Pb trend was contrary to the temperature during the heating period, which may be caused by the fact that as temperature decreased, the intensity of coal combustion for heating increased, which emitted a lot of Pb. Conducting this study plays a significant role in prevention and control of atmospheric pollution and ecological environmental protection.
Secreted proteins play important roles in many crucial biological processes, and can be new agents or targets for drug therapies. Here, we report on the isolation and characterization of a novel human non-classical secreted protein which is encoded by the hypothetical gene C19orf24 (chromosome 19 open reading frame 24). It has no signal peptide, but can still secrete extracellularly despite the presence of the inhibitor brefeldin A (BFA), proving its non-classical secreted protein status. Via subcellular localization using C19orf24 in vivo and transfected pEYFP-Golgi plasmid in Hela cells, C19orf24 was shown not to co-localize in the Golgi apparatus, which suggested that it secretes via a new and unknown pathway. Deglycosylation analysis with PNGase F verified that it has no N-glycosylation modification sites. Via the reverse transcription-PCR method, it was found to be expressed only in the human liver, and preferentially in normal tissue. In addition, C19orf24 was shown to be a recently evolved gene, found only in Homo sapiens and Pan troglodytes. By calculating its synonymous and non-synonymous substitution rate (d S/d N), we found that it experienced a purifying selection, which suggests that C19orf24 may have a special, irreplaceable biological function in the human organism.
MicroRNAs (miRNAs) are a set of small, noncoding RNAs that negatively and post-transcriptionally mediate their respective target mRNAs by directing the target mRNA cleavage or translational repression. Plant miRNAs have been involved in developmental processes and adaption to biotic and abiotic stresses in their environment. The banded leaf and sheath blight (BLSB) caused by Rhizoctonia solani is extremely harmful to maize. To investigate the functions of miRNAs under R. solani inoculation, miRNA expression in R. solani infected maize (Zea mays L.) was profiled using deep sequencing. In total, 41 significantly differentially expressed known miRNAs and 39 novel R. solani-responsive miRNAs were identified, of which 9 identified miRNAs were further validated by qRT-PCR, and 2 important miRNAs were analyzed by in situ hybridization. Target genes were also predicted for these R. solani-responsive miRNAs; most of these putative target genes encoded transcription factors and proteins associated with metabolic processes or stress responses. In addition, the mRNA expression levels of several target genes that negatively correlated with the levels of corresponding miRNAs under R. solani inoculation were validated by qRT-PCR. These findings hypothesized that these miRNAs play an important role in R. solani resistance in maize, highlighting novel molecular mechanisms of R. solani resistance in plants.
Heterotrophic nitrifying bacteria are attracting increasing interest due to their advantages in treatment of wastewater with high nitrogen concentration. In this work, four bacterial isolates (WS-1, WS-4, WS-6, and WS-7) with the capability of simultaneous heterotrophic nitrification and aerobic denitrification from soil, sludge, and water by a fast isolation procedure were studied. Isolates WS-1, WS-6, and WS-7 were identified as Pseudomonas sp. and WS-4 as Agrobacterium sp. based on 16S rRNA gene sequence analysis. All four isolates could utilize ammonia, nitrate, and nitrite as sole nitrogen source and the metabolic characteristics were shown to be related with the genus. In addition, Agrobacterium sp. WS-4 accumulated less nitrate than the three Pseudomonas sp. strains with ammonia as the sole nitrogen source. When nitrate or nitrite was the sole nitrogen source, Agrobacterium sp. did not produce ammonia, and it consumed the least nitrogen compared with the three Pseudomonas sp. isolates. Our studies implied that Pseudomonas sp. strains had great potential in treating high nitrogen in wastewater.
Studies have indicated that a functional polymorphism (Val66Met) in a brain-derived neurotrophic factor (BDNF) gene can influences human cognitive functions and mood disorders. In this study, we examined associations of BDNF Val66Met with attentional bias and personality in an unaffected population. The results showed that BDNF Val66Met was significantly associated with attentional disengagement for positive cueing words in extraverts. Moreover, there was a positive correlation between the dosages of Met allele and attentional disengagement, however, we did not observe any significant influences of BDNF Val66Met on personality traits. These preliminary results indicate that the individual differences in attentional bias for positive words are partially underpinned by BDNF.
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