arXiv subjects

Xing Meng

Publications and source records attributed to Xing Meng.

4 recordsLinked to original sources

arXiv2026

Interface-dependent Phase Transitions and Ultrafast Hydrogen Superionic Diffusion of H2O Ice

High-pressure experiments using diamond anvils have revealed novel properties and phase behavior of H2O under extreme conditions. When contained in diamond-anvil cells, the H2O samples are usually in direct contact with the diamond anvil. However, the extent to which this interface affects measured pressure-induced properties and behavior, including coexistence lines of ice phases, remains unknown. Combining artificial neural network methods and active learning schemes with large-scale molecular dynamics simulations, we elucidate the interfacial effects on various properties of high-pressure ice phases, including superionic states, solid-solid phase transitions, and melting. The results reveal that the presence of this interface can significantly lower the hydrogen superionic transition temperature. Remarkably, the interface can also induce a spontaneous transition from bcc- to fcc-based ice following the inverse Bain mechanism. Further, we redefined a stability field of bcc and fcc ice below the melting line and predicted the existence of fcc ice at much lower pressures than previously thought. More broadly, the results emphasize the importance of interface effects in understanding a wide range of phenomena reported in experimental studies of ice under pressure, including inconsistencies between theoretical and experimental results of this fundamental system.

cond-mat.mtrl-sci↗

arXiv2019

Self-Supervised Contextual Language Representation of Radiology Reports to Improve the Identification of Communication Urgency

Machine learning methods have recently achieved high-performance in biomedical text analysis. However, a major bottleneck in the widespread application of these methods is obtaining the required large amounts of annotated training data, which is resource intensive and time consuming. Recent progress in self-supervised learning has shown promise in leveraging large text corpora without explicit annotations. In this work, we built a self-supervised contextual language representation model using BERT, a deep bidirectional transformer architecture, to identify radiology reports requiring prompt communication to the referring physicians. We pre-trained the BERT model on a large unlabeled corpus of radiology reports and used the resulting contextual representations in a final text classifier for communication urgency. Our model achieved a precision of 97.0%, recall of 93.3%, and F-measure of 95.1% on an independent test set in identifying radiology reports for prompt communication, and significantly outperformed the previous state-of-the-art model based on word2vec representations.

cs.LG↗

arXiv2016

Energy Efficiency in Multiuser Transmission Over Parallel Frequency Channels

Energy efficiency is an important design criterion for wireless communications. When parallel frequency channels are used for multiuser transmission, the channel bandwidths and user power are adjusted to maximize the sum information rate with the bandwidth budget, the transmit power budget, and the user-specific rate requirements. The maximum sum rate is used in measuring the energy efficiency. With fixed or flexible bandwidths of the frequency channels, practical methods are developed to find the total transmit power with the unique optimal resource (bandwidth and power) allocation for maximum energy efficiency. This resource allocation ensures that, while each user's minimum rate requirement is satisfied, all the excess resource of the spectrum and transmit power is dedicated to the one user with the best channel quality. Simulation results validate the optimal solutions of total transmit power and resource allocation that support the energy-efficient multiuser transmission.

cs.IT↗

arXiv2013

Alfven Wave Solar Model (AWSoM): Coronal Heating

We present a new version of the Alfven Wave Solar Model (AWSoM), a global model from the upper chromosphere to the corona and the heliosphere. The coronal heating and solar wind acceleration are addressed with low-frequency Alfven wave turbulence. The injection of Alfven wave energy at the inner boundary is such that the Poynting flux is proportional to the magnetic field strength. The three-dimensional magnetic field topology is simulated using data from photospheric magnetic field measurements. This model does not impose open-closed magnetic field boundaries; those develop self-consistently. The physics includes: (1) The model employs three different temperatures, namely the isotropic electron temperature and the parallel and perpendicular ion temperatures. The firehose, mirror, and ion-cyclotron instabilities due to the developing ion temperature anisotropy are accounted for. (2) The Alfven waves are partially reflected by the Alfven speed gradient and the vorticity along the field lines. The resulting counter-propagating waves are responsible for the nonlinear turbulent cascade. The balanced turbulence due to uncorrelated waves near the apex of the closed field lines and the resulting elevated temperatures are addressed. (3) To apportion the wave dissipation to the three temperatures, we employ the results of the theories of linear wave damping and nonlinear stochastic heating. (4) We have incorporated the collisional and collisionless electron heat conduction. We compare the simulated multi-wavelength EUV images of CR2107 with the observations from STEREO/EUVI and SDO/AIA instruments. We demonstrate that the reflection due to strong magnetic fields in proximity of active regions intensifies the dissipation and observable emission sufficiently.

astro-ph.SR↗