Carbon Dioxide Improves Phosphorus Nutrition by Facilitating the Remobilization of Phosphorus From the Shoot Cell Wall in Rice (Oryza sativa)

Phosphorus (P) starvation leads to increased reutilization of cell wall P in rice (Oryza sativa). Carbon dioxide (CO2) is involved not only in plant growth and development but also in the response to abiotic stresses. However, it remains unclear whether CO2 affects the reutilization of cell wall P in rice when subjected to P deficiency. In the present study, elevated CO2 (600 μl·L−1) significantly increased the soluble P content in shoots when compared with ambient CO2 (400 μl·L−1). This positive effect was accompanied by an increase of pectin content, as well as an increase of pectin methylesterase (PME) activity, which results in P release from the shoot cell wall, making it available for plant growth. P deficiency significantly induced the expression of phosphate transporter genes (OsPT2, OsPT6, and OsPT8) and decreased the P content in the xylem sap, but elevated CO2 had no further effect, indicating that the increased soluble P content observed in shoots under elevated CO2 is attributable to the reutilization of shoot cell wall P. Elevated CO2 further increased the P deficiency-induced ethylene production in the shoots, and the addition of the ethylene precursor 1-amino-cyclopropane-1-carboxylic acid (ACC) mimicked this effect, while the addition of the ethylene inhibitor aminoethoxyvinylglycine (AVG) abolished this effect. These results further support the role of ethylene in the alleviation of P deficiency under elevated CO2. Taken together, our results indicate that the improvement of P nutrition in rice by elevated CO2 is mediated by increasing the shoot cell wall pectin content and PME activity, possibly via the ethylene signaling pathway

Improving the sensitivity of a near-infrared nanocomposite photodetector by enhancing trap induced hole injection

We report the enhancement of the photoconductive gain of nanocomposite near-infrared photodetectors by a zinc oxide nanoparticles (ZnO NPs) rich surface at the nanocomposite/cathode interface. An argon plasma etching process was used to remove polymer at the surface of nanocomposite films, which resulted in a ZnO NPs rich surface. The other way is to spin-coat a thin layer of ZnO NPs onto the nanocomposite layer. The ZnO NPs rich surface, which acts as electron traps to induce secondary hole injection under reverse bias, increased hole injection, and thus the external quantum efficiency by 2–3 times. The darkcurrent declined one order of magnitude simultaneously as a result of etching the top nanocomposite layer. The specific detectivity at 800 nm was increased by 7.4 times to 1.11x1010 Jones due to the simultaneously suppressed noise and enhanced gain

Improving the sensitivity of a near-infrared nanocomposite photodetector by enhancing trap induced hole injection

We report the enhancement of the photoconductive gain of nanocomposite near-infrared photodetectors by a zinc oxide nanoparticles (ZnO NPs) rich surface at the nanocomposite/cathode interface. An argon plasma etching process was used to remove polymer at the surface of nanocomposite films, which resulted in a ZnO NPs rich surface. The other way is to spin-coat a thin layer of ZnO NPs onto the nanocomposite layer. The ZnO NPs rich surface, which acts as electron traps to induce secondary hole injection under reverse bias, increased hole injection, and thus the external quantum efficiency by 2–3 times. The darkcurrent declined one order of magnitude simultaneously as a result of etching the top nanocomposite layer. The specific detectivity at 800 nm was increased by 7.4 times to 1.11x1010 Jones due to the simultaneously suppressed noise and enhanced gain

Methanotrophic abundance and community fingerprint in pine and tea plantation soils as revealed by molecular methods

Understanding the community structure of methane-oxidizing bacteria (methanotrophs) is important to assess the microbial oxidation of the greenhouse gas methane (CH4) in soil under different land uses. Soil samples were collected from two plantation plots of pine and tea in southern China. Methanotrophic abundance was quantified with quantitative real-time polymerase chain reaction (qPCR) based on the 16S rRNA and pmoA genes, and the community fingerprint was characterized with denaturing gradient gel electrophoresis (DGGE) targeting the pmoA gene. No significant difference in the gene copy numbers of methanotrophs was found between the pine and tea land-use, regardless of 16S rRNA and pmoA genes. Higher abundance of type I (1.35 vs 1.66×108 copie g-1 soil) over type II methanotrophs (8.59 vs 10.9 × 107) were found both in pine and tea plantation soils. Apparent differences in methanotrophic community fingerprint were observed between the pine and tea treatments. Correlations analysis between methanotrophic abundance and soil characteristics, combining with canonial correspondence analysis (CCA) regarding community fingerprint and environmental parameters indicated that soil pH and available phosphorus were the most important factors potentially affecting the methanotrophic community diversity in the acidic red soil.Key words: Denaturing gradient gel electrophoresis (DGGE), land use, methanotrophs, pmoA gene, quantitative real-time PCR (qPCR)

Quantity Management of Stock Based on BOM

It is an instinct requirement of the enterprise management to lower the cost so that the enterprise can optimize the asset efficiency. To enhance competition ability and enlarge the market share, enterprises must have a good inventory management system. In this paper, two solutions of inventory management based on bill of material (BOM) have been discussed. One is the accurate quantity and time that globally decided by primary equation of inventory management and the form of material requirement planning (MRP). The other is the stock requirement quantity and the detail structure which is implemented by compound BOM structure. A systematic and quantitative management method for trivial and heavy stock management had been discussed in this paper

PPCR: Learning Pyramid Pixel Context Recalibration Module for Medical Image Classification

Spatial attention mechanism has been widely incorporated into deep convolutional neural networks (CNNs) via long-range dependency capturing, significantly lifting the performance in computer vision, but it may perform poorly in medical imaging. Unfortunately, existing efforts are often unaware that long-range dependency capturing has limitations in highlighting subtle lesion regions, neglecting to exploit the potential of multi-scale pixel context information to improve the representational capability of CNNs. In this paper, we propose a practical yet lightweight architectural unit, Pyramid Pixel Context Recalibration (PPCR) module, which exploits multi-scale pixel context information to recalibrate pixel position in a pixel-independent manner adaptively. PPCR first designs a cross-channel pyramid pooling to aggregate multi-scale pixel context information, then eliminates the inconsistency among them by the well-designed pixel normalization, and finally estimates per pixel attention weight via a pixel context integration. PPCR can be flexibly plugged into modern CNNs with negligible overhead. Extensive experiments on five medical image datasets and CIFAR benchmarks empirically demonstrate the superiority and generalization of PPCR over state-of-the-art attention methods. The in-depth analyses explain the inherent behavior of PPCR in the decision-making process, improving the interpretability of CNNs.Comment: 10 page

Identification of a laccase Glac15 from Ganoderma lucidum 77002 and its application in bioethanol production

Background Laccases have potential applications in detoxification of lignocellulosic biomass after thermochemical pretreatment and production of value-added products or biofuels from renewable biomass. However, their application in large-scale industrial and environmental processes has been severely thwarted by the high cost of commercial laccases. Therefore, it is necessary to identify new laccases with lower cost but higher activity to detoxify lignocellulosic hydrolysates and better efficiency to produce biofuels such as bioethanol. Laccases from Ganoderma lucidum represent proper candidates in processing of lignocellulosic biomass. Results G. lucidum 77002 produces three laccase isoenzymes with a total laccase activity of 141.1 U/mL within 6 days when using wheat bran and peanut powder as energy sources in liquid culture medium. A new isoenzyme named Glac15 was identified, purified, and characterized. Glac15 possesses an optimum pH of 4.5 to 5.0 and a temperature range of 45°C to 55°C for the substrates tested. It was stable at pH values ranging from 5.0 to 7.0 and temperatures lower than 55°C, with more than 80% activity retained after incubation for 2 h. When used in bioethanol production process, 0.05 U/mL Glac15 removed 84% of the phenolic compounds in prehydrolysate, and the yeast biomass reached 11.81 (optimal density at 600 nm (OD600)), compared to no growth in the untreated one. Addition of Glac15 before cellulase hydrolysis had no significant effect on glucose recovery. However, ethanol yield were improved in samples treated with laccases compared to that in control samples. The final ethanol concentration of 9.74, 10.05, 10.11, and 10.81 g/L were obtained from samples containing only solid content, solid content treated with Glac15, solid content containing 50% prehydrolysate, and solid content containing 50% prehydrolysate treated with Glac15, respectively. Conclusions The G. lucidum laccase Glac15 has potentials in bioethanol production industry