Transport properties of dense deuterium-tritium plasmas

Consistent descriptions of the equation of states, and information about transport coefficients of deuterium-tritium mixture are demonstrated through quantum molecular dynamic (QMD) simulations (up to a density of 600 g/cm$^{3}$ and a temperature of $10^{4}$ eV). Diffusion coefficients and viscosity are compared with one component plasma model in different regimes from the strong coupled to the kinetic one. Electronic and radiative transport coefficients, which are compared with models currently used in hydrodynamic simulations of inertial confinement fusion, are evaluated up to 800 eV. The Lorentz number is also discussed from the highly degenerate to the intermediate region.Comment: 4 pages, 3 figure

Bis(melaminium) tartrate dihydrate

In the title compound, 2C3H7N6 +·C4H4O6 2−·2H2O, in which the complete anion is generated by crystallographic twofold symmetry, there are O—H⋯O, N—H⋯O and N—H⋯N hydrogen-bonding inter­actions between neighbouring moieties, forming layers parallel to the bc plane. In addition, π–π contacts [centroid–centroid distance = 3.6541 (9) Å] between the six-membered rings of the melamine cations are observed

Surgical treatment of multivalvular endocarditis: Twenty-one–year single center experience

ObjectiveLittle information is available about surgical outcomes in patients with multivalvular endocarditis. The aim of this article is to review the 21-year experience with surgical treatment of patients with multivalvular endocarditis at our institution and, in particular, to determine the incidence, pathologic status, diagnosis, surgical strategies, and outcomes of patients with this disease.MethodsFrom January 1986 to December 2006, a total of 48 patients (40 men, 8 women), with a mean age of 42 ± 12 years, underwent surgery for multivalvular endocarditis. Endocarditis was active in 32 patients and healed in 16. Preoperative transthoracic echocardiographic evaluation was performed in all 48 patients with addition of transesophageal echocardiography in 22 (45.8%). Intraoperative findings showed that the endocarditis involved mostly the mitral and aortic valves (40/48 patients). Triple or quadruple valve involvement was found in 1 and 2 patients, respectively. Preoperative, perioperative, and postoperative data were retrospectively analyzed and risk factors for early and late survival were determined.ResultsIn only 24 (50.0%) patients was multivalvular endocarditis diagnosed by preoperative transthoracic echocardiography; 17 (77.3%) patients had multivalvular endocarditis confirmed by preoperative transesophageal echocardiography. The 30-day hospital mortality was 12.5% (n = 6). Preoperative renal failure, New York Heart Association class IV, and emergency surgery were identified as independent risk factors for hospital mortality. Overall long-term survival was 74% ± 6% at 5 years and 62% ± 3% at 10 years. Multivariate analysis revealed that renal failure and recurrent endocarditis were associated with increased late mortality. Ten-year freedom from recurrent endocarditis was 74% ± 5% and 10-year freedom from reoperation was 73% ± 6%.ConclusionsIn our institution, multivalvular endocarditis was diagnosed by transthoracic echocardiography in only half of the patients. Intraoperative transesophageal echocardiography provided a more effective means to identify this disease. Radical resection of all infected tissues for patients with multivalvular endocarditis and additional intraoperative interventions, depending on the intraoperative pathologic condition, produced satisfactory in-hospital and long-term results, similar to those in patients with a single infected heart valve

Single-cell RNA-seq data analysis using graph autoencoders and graph attention networks

With the development of high-throughput sequencing technology, the scale of single-cell RNA sequencing (scRNA-seq) data has surged. Its data are typically high-dimensional, with high dropout noise and high sparsity. Therefore, gene imputation and cell clustering analysis of scRNA-seq data is increasingly important. Statistical or traditional machine learning methods are inefficient, and improved accuracy is needed. The methods based on deep learning cannot directly process non-Euclidean spatial data, such as cell diagrams. In this study, we developed scGAEGAT, a multi-modal model with graph autoencoders and graph attention networks for scRNA-seq analysis based on graph neural networks. Cosine similarity, median L1 distance, and root-mean-squared error were used to measure the gene imputation performance of different methods for comparison with scGAEGAT. Furthermore, adjusted mutual information, normalized mutual information, completeness score, and Silhouette coefficient score were used to measure the cell clustering performance of different methods for comparison with scGAEGAT. Experimental results demonstrated promising performance of the scGAEGAT model in gene imputation and cell clustering prediction on four scRNA-seq data sets with gold-standard cell labels

Testing and Data Reduction of the Chinese Small Telescope Array (CSTAR) for Dome A, Antarctica

The Chinese Small Telescope ARray (hereinafter CSTAR) is the first Chinese astronomical instrument on the Antarctic ice cap. The low temperature and low pressure testing of the data acquisition system was carried out in a laboratory refrigerator and on the 4500m Pamirs high plateau, respectively. The results from the final four nights of test observations demonstrated that CSTAR was ready for operation at Dome A, Antarctica. In this paper we present a description of CSTAR and the performance derived from the test observations.Comment: Accepted Research in Astronomy and Astrophysics (RAA) 1 Latex file and 20 figure