Plants transition through juvenile and adult phases of vegetative development in a process known as vegetative phase change (VPC). In poplars (genus We examined developmental morphology of seed‐grown and In seed‐grown plants, most traits changed from node‐to‐node during the first 3 months of development but remained constant after node 25. Many traits remained unchanged in clones over‐expressing miR156, or were enhanced when miR156 was lowered, demonstrating their natural progression is regulated by the miR156/SPL pathway. The characteristic leaf fluttering of Vegetative development in plants grown from culture mirrored that of seed‐grown plants, allowing direct comparison between plants often used in research and those found in nature. These results provide a foundation for further research on the role of VPC in the ecology and evolution of this economically important genus.
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Summary Populus ) the differences between these stages are subtle, making it difficult to determine when this transition occurs. Previous studies of VPC in poplars have relied on plants propagatedin vitro , leaving the natural progression of this process unknown.in vitro derivedPopulus tremula × alba (clone 717‐1B4), and compared the phenotype of these to transgenics with manipulated miR156 expression, the master regulator of VPC.Populus is one of these miR156‐regulated traits. -
null (Ed.)Abstract Seismograms are convolution results between seismic sources and the media that seismic waves propagate through, and, therefore, the primary observations for studying seismic source parameters and the Earth interior. The routine earthquake location and travel-time tomography rely on accurate seismic phase picks (e.g., P and S arrivals). As data increase, reliable automated seismic phase-picking methods are needed to analyze data and provide timely earthquake information. However, most traditional autopickers suffer from low signal-to-noise ratio and usually require additional efforts to tune hyperparameters for each case. In this study, we proposed a deep-learning approach that adapted soft attention gates (AGs) and recurrent-residual convolution units (RRCUs) into the backbone U-Net for seismic phase picking. The attention mechanism was implemented to suppress responses from waveforms irrelevant to seismic phases, and the cooperating RRCUs further enhanced temporal connections of seismograms at multiple scales. We used numerous earthquake recordings in Taiwan with diverse focal mechanisms, wide depth, and magnitude distributions, to train and test our model. Setting the picking errors within 0.1 s and predicted probability over 0.5, the AG with recurrent-residual convolution unit (ARRU) phase picker achieved the F1 score of 98.62% for P arrivals and 95.16% for S arrivals, and picking rates were 96.72% for P waves and 90.07% for S waves. The ARRU phase picker also shown a great generalization capability, when handling unseen data. When applied the model trained with Taiwan data to the southern California data, the ARRU phase picker shown no cognitive downgrade. Comparing with manual picks, the arrival times determined by the ARRU phase picker shown a higher consistency, which had been evaluated by a set of repeating earthquakes. The arrival picks with less human error could benefit studies, such as earthquake location and seismic tomography.more » « less
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ABSTRACT A recent publication discovered one of the largest filamentary neutral hydrogen features dubbed Cattail from high-resolution Five-hundred-meter Aperture Spherical radio Telescope observations that might be a new galactic arm of the Milky Way. We evaluate the turbulent and phase properties of Cattail via the newly developed Velocity Decomposition Algorithm and Force Balancing Model. We discover that if there exists a phase transition, then Cattail is unlikely in the cold neutral media phase. We also show that the Cattail is two disjoint features in caustics space, suggesting that the Cattail has two different turbulent systems. We check the spectra of the individual system separated via VDA to confirm this argument. We do not exclude the existence of smaller scale cold media being embedded within this structure.
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We investigate a model of electrons with random and all-to-all hopping and spin exchange interactions, with a constraint of no double occupancy. The model is studied in a Sachdev–Ye–Kitaev-like large-
M limit with SU(M ) spin symmetry. The saddle-point equations of this model are similar to approximate dynamic mean-field equations of realistic, nonrandom,t -J models. We use numerical studies on both real and imaginary frequency axes, along with asymptotic analyses, to establish the existence of a critical non–Fermi-liquid metallic ground state at large doping, with the spin correlation exponent varying with doping. This critical solution possesses a time-reparameterization symmetry, akin to Sachdev–Ye–Kitaev (SYK) models, which contributes a linear-in-temperature resistivity over the full range of doping where the solution is present. It is therefore an attractive mean-field description of the overdoped region of cuprates, where experiments have observed a linear-T resistivity in a broad region. The critical metal also displays a strong particle–hole asymmetry, which is relevant to Seebeck coefficient measurements. We show that the critical metal has an instability to a low-doping spin-glass phase and compute a critical doping value. We also describe the properties of this metallic spin-glass phase.
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/LMWT.2022.3230039
