1,615 research outputs found
1-Benzyl-2,3-dihydroquinolin-4(1H)-one
In the title compound, C16H15NO, the two aromatic rings are approximately perpendicular; the carbonyl group is twisted out of the adjacent benzene ring by 14.8 (2)°. In the heterocyclic ring, the C atom linked to the carbonyl group and the C atom linked to the N atom have opposite deviations of 0.467 (5) and 0.184 (4) Å, respectively, from the plane of the benzene ring. The N atom lies approximately in the plane of the phenyl ring. There are no conventional hydrogen bonds; the packing of molecules in the crystal structure is stabilized by van der Waals forces
The cosmic ray test of MRPCs for the BESIII ETOF upgrade
In order to improve the particle identification capability of the Beijing
Spectrometer III (BESIII),t is proposed to upgrade the current endcap
time-of-flight (ETOF) detector with multi-gap resistive plate chamber (MRPC)
technology. Aiming at extending ETOF overall time resolution better than 100ps,
the whole system including MRPC detectors, new-designed Front End Electronics
(FEE), CLOCK module, fast control boards and time to digital modules (TDIG),
was built up and operated online 3 months under the cosmic ray. The main
purposes of cosmic ray test are checking the detectors' construction quality,
testing the joint operation of all instruments and guaranteeing the performance
of the system. The results imply MRPC time resolution better than 100,
efficiency is about 98 and the noise rate of strip is lower than
1() at normal threshold range, the details are discussed and
analyzed specifically in this paper. The test indicates that the whole ETOF
system would work well and satisfy the requirements of upgrade
Development of marker-free transgenic Jatropha plants with increased levels of seed oleic acid
<p>Abstract</p> <p>Background</p> <p><it>Jatropha curcas </it>is recognized as a new energy crop due to the presence of the high amount of oil in its seeds that can be converted into biodiesel. The quality and performance of the biodiesel depends on the chemical composition of the fatty acids present in the oil. The fatty acids profile of the oil has a direct impact on ignition quality, heat of combustion and oxidative stability. An ideal biodiesel composition should have more monounsaturated fatty acids and less polyunsaturated acids. Jatropha seed oil contains 30% to 50% polyunsaturated fatty acids (mainly linoleic acid) which negatively impacts the oxidative stability and causes high rate of nitrogen oxides emission.</p> <p>Results</p> <p>The enzyme 1-acyl-2-oleoyl-sn-glycero-3-phosphocholine delta 12-desaturase (FAD2) is the key enzyme responsible for the production of linoleic acid in plants. We identified three putative <it>delta </it><it>12 </it><it>fatty acid desaturase </it>genes in <it>Jatropha </it>(<it>JcFAD2s</it>) through genome-wide analysis and downregulated the expression of one of these genes, <it>JcFAD2-1</it>, in a seed-specific manner by RNA interference technology. The resulting <it>JcFAD2-1 </it>RNA interference transgenic plants showed a dramatic increase of oleic acid (> 78%) and a corresponding reduction in polyunsaturated fatty acids (< 3%) in its seed oil. The control <it>Jatropha </it>had around 37% oleic acid and 41% polyunsaturated fatty acids. This indicates that FAD2-1 is the major enzyme responsible for converting oleic acid to linoleic acid in <it>Jatropha</it>. Due to the changes in the fatty acids profile, the oil of the <it>JcFAD2-1 </it>RNA interference seed was estimated to yield a cetane number as high as 60.2, which is similar to the required cetane number for conventional premium diesel fuels (60) in Europe. The presence of high seed oleic acid did not have a negative impact on other <it>Jatropha </it>agronomic traits based on our preliminary data of the original plants under greenhouse conditions. Further, we developed a marker-free system to generate the transgenic <it>Jatropha </it>that will help reduce public concerns for environmental issues surrounding genetically modified plants.</p> <p>Conclusion</p> <p>In this study we produced seed-specific <it>JcFAD2-1 </it>RNA interference transgenic <it>Jatropha </it>without a selectable marker. We successfully increased the proportion of oleic acid versus linoleic in <it>Jatropha </it>through genetic engineering, enhancing the quality of its oil.</p
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
Large-scale models pre-trained on large-scale datasets have profoundly
advanced the development of deep learning. However, the state-of-the-art models
for medical image segmentation are still small-scale, with their parameters
only in the tens of millions. Further scaling them up to higher orders of
magnitude is rarely explored. An overarching goal of exploring large-scale
models is to train them on large-scale medical segmentation datasets for better
transfer capacities. In this work, we design a series of Scalable and
Transferable U-Net (STU-Net) models, with parameter sizes ranging from 14
million to 1.4 billion. Notably, the 1.4B STU-Net is the largest medical image
segmentation model to date. Our STU-Net is based on nnU-Net framework due to
its popularity and impressive performance. We first refine the default
convolutional blocks in nnU-Net to make them scalable. Then, we empirically
evaluate different scaling combinations of network depth and width, discovering
that it is optimal to scale model depth and width together. We train our
scalable STU-Net models on a large-scale TotalSegmentator dataset and find that
increasing model size brings a stronger performance gain. This observation
reveals that a large model is promising in medical image segmentation.
Furthermore, we evaluate the transferability of our model on 14 downstream
datasets for direct inference and 3 datasets for further fine-tuning, covering
various modalities and segmentation targets. We observe good performance of our
pre-trained model in both direct inference and fine-tuning. The code and
pre-trained models are available at https://github.com/Ziyan-Huang/STU-Net
L-band fiber laser mode-locked by all-polarization maintaining nonlinear polarization rotation
For the first time in the soliton regime, we demonstrated an L-band fiber laser mode-locked by all polarization-maintaining nonlinear polarization rotation. The self-starting laser centered at 1586.4 nm with long-term stability
6G Network Operation Support System
6G is the next-generation intelligent and integrated digital information
infrastructure, characterized by ubiquitous interconnection, native
intelligence, multi-dimensional perception, global coverage, green and
low-carbon, native network security, etc. 6G will realize the transition from
serving people and people-things communication to supporting the efficient
connection of intelligent agents, and comprehensively leading the digital,
intelligent and green transformation of the economy and the society. As the
core support system for mobile communication network, 6G OSS needs to achieve
high-level network automation, intelligence and digital twinning capabilities
to achieve end-to-end autonomous network operation and maintenance, support the
operation of typical 6G business scenarios and play a greater social
responsibility in the fields of environment, society, and governance (ESG).This
paper provides a detailed introduction to the overall vision, potential key
technologies, and functional architecture of 6G OSS . It also presents an
evolutionary roadmap and technological prospects for the OSS from 5G to 6G.Comment: 103 pages, 20 figures, 52 references (chinese version
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