RNAi-directed downregulation of OsBADH2 results in aroma (2-acetyl-1-pyrroline) production in rice (Oryza sativa L.)

<p>Abstract</p> <p>Background</p> <p>Aromatic rice is popular worldwide because of its characteristic fragrance. Genetic studies and physical fine mapping reveal that a candidate gene (<it>fgr</it>/<it>OsBADH2</it>) homologous to <it>betaine aldehyde dehydrogenase </it>is responsible for aroma metabolism in fragrant rice varieties, but the direct evidence demonstrating the functions of <it>OsBADH2 </it>is lacking. To elucidate the physiological roles of <it>OsBADH2</it>, sequencing approach and RNA interference (RNAi) technique were employed to analyze allelic variation and functions of <it>OsBADH2 </it>gene in aroma production. Semi-quantitative, real-time reverse transcription-polymerase chain reaction (RT-PCR), as well as gas chromatography-mass spectrometry (GC-MS) were conducted to determine the expression levels of <it>OsBADH2 </it>and the fragrant compound in wild type and transgenic <it>OsBADH2</it>-RNAi repression lines, respectively.</p> <p>Results</p> <p>The results showed that multiple mutations identical to <it>fgr </it>allele occur in the 13 fragrant rice accessions across China; <it>OsBADH2 </it>is expressed constitutively, with less expression abundance in mature roots; the disrupted <it>OsBADH2 </it>by RNA interference leads to significantly increased 2-acetyl-1-pyrroline production.</p> <p>Conclusion</p> <p>We have found that the altered expression levels of <it>OsBADH2 </it>gene influence aroma accumulation, and the prevalent aromatic allele probably has a single evolutionary origin.</p

Multi-Technology Driven R&D Cost Improvement Scheme and Application Utility of EESP in Energy-Intensive Manufacturing Industry

Facing the sustainable use of electric power resources, many countries in the world focus on the R&D investment and application of electrochemical energy storage projects (i.e., EESP). However, the high R&D cost of EESP has been hindering large-scale industrial promotion in the energy-intensive manufacturing industry represented by the tobacco industry. Reducing and controlling the R&D cost has become an urgent problem to be solved. In this context, this paper innovatively proposes a multi-technology driven R&D cost improvement scheme, which integrates WBS (i.e., Work Breakdown Structure), EVM (i.e., Earned Value Method), BD (i.e., Big Data), and ML (i.e., Machine Learning) methods. Especially, the influence of R&D cost improvement on EESP application performance is discussed through mathematical model analysis. The research indicates that reducing EESP R&D costs can significantly improve the stability of EESP power supply, and ultimately improve the application value of EESP in energy-intensive manufacturing industries. The R&D cost management scheme and technical method proposed in this paper have important theoretical guiding values and practical significance for accelerating the large-scale application of EESP

Vibration Response Characteristics of the Cross Tunnel Structure

It is well known that the tunnel structure will lose its function under the long-term repeated function of the vibration effect. A prime example is the Xi’an cross tunnel structure (CTS) of Metro Line 2 and the Yongningmen tunnel, where the vibration response of the tunnel vehicle load and metro train load to the structure of shield tunnel was analyzed by applying the three-dimensional (3D) dynamic finite element model. The effect of the train running was simulated by applying the time-history curves of vibration force of the track induced by wheel axles, using the fitted formulas for vehicle and train vibration load. The characteristics and the spreading rules of vibration response of metro tunnel structure were researched from the perspectives of acceleration, velocity, displacement, and stress. It was found that vehicle load only affects the metro tunnel within 14 m from the centre, and the influence decreases gradually from vault to spandrel, haunch, and springing. The high-speed driving effect of the train can be divided into the close period, the rising period, the stable period, the declining period, and the leaving period. The stress at haunch should be carefully considered. The research results presented for this case study provide theoretical support for the safety of vibration response of Metro Line 2 structure

Structural Response of the Metro Tunnel under Local Dynamic Water Environment in Loess Strata

The reasons, prevention, and control of loess disaster are of great concern in practice. In recent years, Xi’an city, China, has taken the leadership in large-scale construction of subway lines in the loess strata. To study the structural response of the tunnel in loess region under local hydrodynamic environment, an experimental testing in 1g as well as a numerical simulation were performed, in which the achieved results were verified and were found to be in good agreement. Furthermore, the results showed that when the water outlet point is above the lining, the overall stress of the lining is “peanut shell,” as the water pressure of the outlet point decreases, the tensile stress of the top and bottom of the lining increases, while the compressive stress on both sides decreases; the channel form of the flow to the lining changes with the variation of the position of the water outlet point. It is worth mentioning that in the process of water gushing, the closer to the water source, the greater surface subsidence is, and there is a positive correlation between water pressure and surface subsidence. This study is of significant benchmark for the construction, maintenance, and prevention of tunnel in loess strata under the influence of water environment

Progress of Single-Crystal Nickel-Cobalt-Manganese Cathode Research

The booming electric vehicle industry continues to place higher requirements on power batteries related to economic-cost, power density and safety. The positive electrode materials play an important role in the energy storage performance of the battery. The nickel-rich NCM (LiNixCoyMnzO2 with x + y + z = 1) materials have received increasing attention due to their high energy density, which can satisfy the demand of commercial-grade power batteries. Prominently, single-crystal nickel-rich electrodes with s unique micron-scale single-crystal structure possess excellent electrochemical and mechanical performance, even when tested at high rates, high cut-off voltages and high temperatures. In this review, we outline in brief the characteristics, problems faced and countermeasures of nickel-rich NCM materials. Then the distinguishing features and main synthesis methods of single-crystal nickel-rich NCM materials are summarized. Some existing issues and modification methods are also discussed in detail, especially the optimization strategies under harsh conditions. Finally, an outlook on the future development of single-crystal nickel-rich materials is provided. This work is expected to provide some reference for research on single-crystal nickel-rich ternary materials with high energy density, high safety levels, long-life, and their contribution to sustainable development

A Surface Defect Inspection Model via Rich Feature Extraction and Residual-Based Progressive Integration CNN

Surface defect inspection is vital for the quality control of products and the fault diagnosis of equipment. Defect inspection remains challenging due to the low level of automation in some manufacturing plants and the difficulty in identifying defects. To improve the automation and intelligence levels of defect inspection, a CNN model is proposed for the high-precision defect inspection of USB components in the actual demands of factories. First, the defect inspection system was built, and a dataset named USB-SG, which contained five types of defects—dents, scratches, spots, stains, and normal—was established. The pixel-level defect ground-truth annotations were manually marked. This paper puts forward a CNN model for solving the problem of defect inspection tasks, and three strategies are proposed to improve the model’s performance. The proposed model is built based on the lightweight SqueezeNet network, and a rich feature extraction block is designed to capture semantic and detailed information. Residual-based progressive feature integration is proposed to fuse the extracted features, which can reduce the difficulty of model fine-tuning and improve the generalization ability. Finally, a multi-step deep supervision scheme is proposed to supervise the feature integration process. The experiments on the USB-SG dataset prove that the model proposed in this paper has better performance than that of other methods, and the running speed can meet the real-time demand, which has broad application prospects in the industrial inspection scene