Phase structure of lattice QCD with two flavors of Wilson quarks at finite temperature and chemical potential

We present results for phase structure of lattice QCD with two degenerate flavors ($N_f=2$) of Wilson quarks at finite temperature $T$ and small baryon chemical potential $\mu_B$. Using the imaginary chemical potential for which the fermion determinant is positive, we perform simulations at points where the ratios of pseudo-scalar meson mass to the vector meson mass $m_\pi/m_\rho$ are between $0.943(3)$ and $0.899(4)$ as well as in the quenched limit. By analytic continuation to real quark chemical potential $\mu$, we obtain the transition temperature as a function of small $\mu_B$. We attempt to determine the nature of transition at imaginary chemical potential by histogram, MC history, and finite size scaling. In the infinite heavy quark limit, the transition is of first order. At intermediate values of quark mass $m_q$ corresponding to the ratio of $m_\pi/m_\rho$ in the range from $0.943(3)$ to $0.899(4)$ at $a\mu_I=0.24$, the MC simulations show absence of phase transition.Comment: 10 pages, 17 figures;16 figures;9 pages,10 figures;10 pages,11 figure

Multistaged discharge constructing heterostructure with enhanced solid-solution behavior for long-life lithium-oxygen batteries.

Inferior charge transport in insulating and bulk discharge products is one of the main factors resulting in poor cycling stability of lithium-oxygen batteries with high overpotential and large capacity decay. Here we report a two-step oxygen reduction approach by pre-depositing a potassium carbonate layer on the cathode surface in a potassium-oxygen battery to direct the growth of defective film-like discharge products in the successive cycling of lithium-oxygen batteries. The formation of defective film with improved charge transport and large contact area with a catalyst plays a critical role in the facile decomposition of discharge products and the sustained stability of the battery. Multistaged discharge constructing lithium peroxide-based heterostructure with band discontinuities and a relatively low lithium diffusion barrier may be responsible for the growth of defective film-like discharge products. This strategy offers a promising route for future development of cathode catalysts that can be used to extend the cycling life of lithium-oxygen batteries

On the Generation of Medical Question-Answer Pairs

Question answering (QA) has achieved promising progress recently. However, answering a question in real-world scenarios like the medical domain is still challenging, due to the requirement of external knowledge and the insufficient quantity of high-quality training data. In the light of these challenges, we study the task of generating medical QA pairs in this paper. With the insight that each medical question can be considered as a sample from the latent distribution of questions given answers, we propose an automated medical QA pair generation framework, consisting of an unsupervised key phrase detector that explores unstructured material for validity, and a generator that involves a multi-pass decoder to integrate structural knowledge for diversity. A series of experiments have been conducted on a real-world dataset collected from the National Medical Licensing Examination of China. Both automatic evaluation and human annotation demonstrate the effectiveness of the proposed method. Further investigation shows that, by incorporating the generated QA pairs for training, significant improvement in terms of accuracy can be achieved for the examination QA system.Comment: AAAI 202

Dynamic Quality Metric Oriented Error-bounded Lossy Compression for Scientific Datasets

With the ever-increasing execution scale of high performance computing (HPC) applications, vast amounts of data are being produced by scientific research every day. Error-bounded lossy compression has been considered a very promising solution to address the big-data issue for scientific applications because it can significantly reduce the data volume with low time cost meanwhile allowing users to control the compression errors with a specified error bound. The existing error-bounded lossy compressors, however, are all developed based on inflexible designs or compression pipelines, which cannot adapt to diverse compression quality requirements/metrics favored by different application users. In this paper, we propose a novel dynamic quality metric oriented error-bounded lossy compression framework, namely QoZ. The detailed contribution is three-fold. (1) We design a novel highly-parameterized multi-level interpolation-based data predictor, which can significantly improve the overall compression quality with the same compressed size. (2) We design the error-bounded lossy compression framework QoZ based on the adaptive predictor, which can auto-tune the critical parameters and optimize the compression result according to user-specified quality metrics during online compression. (3) We evaluate QoZ carefully by comparing its compression quality with multiple state-of-the-arts on various real-world scientific application datasets. Experiments show that, compared with the second-best lossy compressor, QoZ can achieve up to 70% compression ratio improvement under the same error bound, up to 150% compression ratio improvement under the same PSNR, or up to 270% compression ratio improvement under the same SSIM

MDZ: An Efficient Error-Bounded Lossy Compressor for Molecular Dynamics

Molecular dynamics (MD) has been widely used in today\u27s scientific research across multiple domains including materials science, biochemistry, biophysics, and structural biology. MD simulations can produce extremely large amounts of data in that each simulation could involve a large number of atoms (up to trillions) for a large number of timesteps (up to hundreds of millions). In this paper, we perform an in-depth analysis of a number of MD simulation datasets and then develop an efficient error-bounded lossy compressor that can significantly improve the compression ratios. The contributions are fourfold. (1) We characterize a number of MD datasets and summarize two commonly used execution models. (2) We develop an adaptive error-bounded lossy compression framework (called MDZ), which can optimize the compression for both execution models adaptively by taking advantage of their specific characteristics. (3) We compare our solution with six other state-of-the-art related works by using three MD simulation packages each with multiple configurations. Experiments show that our solution has up to 233 % higher compression ratios than the second-best lossy compressor in most cases. (4) We demonstrate that MDZ is fully capable of handling particle data beyond MD simulations

ASSESSING THE IMPACT OF INNOVATION GENERATION ON ADAPTABILITY IN ELECTRONIC SUPPLY CHAINS

This paper aims to examine how information technology infrastructure flexibility interacts with innovation generation influencing the adaptability in electronic supply chains. A novel research model comprises three constructs and three research hypotheses, with innovation generation as mediating constructs. The empirical study is conducted on electronic supply chains, with data collected from Taiwan’s manufacturing firms. The findings of the study provide useful insights into how electronic supply chain members should reinforce their open innovation via enhancing the innovation generation and in turn enhance the adaptability for the electronic supply chain as a whole

An unprecedented 2D covalent organic framework with an htb net topology.

A 2D imine-linked COF with a hitherto unreported htb type topology was synthesized from a linear diamine linker and a judiciously designed tetra-aldehyde building block. This work opens the door to the development of COFs with unprecedented topologies and may broaden the scope of COF functional materials by pore size and pore surface engineering