Neutron-proton effective mass splitting in neutron-rich matter

Nucleon effective masses in neutron-rich matter are studied with the relativistic Brueckner-Hartree-Fock (RBHF) theory in the full Dirac space. The neutron and proton effective masses for symmetric nuclear matter are 0.80, which agrees well with the empirical values. In neutron-rich matter, the effective mass of the neutron is found larger than that of the proton, and the neutron-proton effective mass splittings at the empirical saturation density are predicted as $0.187\alpha$ with $\alpha$ being the isospin asymmetry parameter. The result is compared to other ab initio calculations and is consistent with the constraints from the nuclear reaction and structure measurements, such as the nucleon-nucleus scattering, the giant resonances of $^{208}$Pb, and the Hugenholtz-Van Hove theorem with systematics of nuclear symmetry energy and its slope. The predictions of the neutron-proton effective mass splitting from the RBHF theory in the full Dirac space might be helpful to constrain the isovector parameters in phenomenological density functionals.Comment: 14 pages, 4 figure

Petrogenesis of the quartz diorite from the Lietinggang-Leqingla Pb-Zn-Fe-Cu- (Mo) deposit in southern Tibet: implications for the genesis of a skarn-type polymetallic deposit in the Tibetan-Himalayan collisional orogen

publishedVersio

RSG: Fast Learning Adaptive Skills for Quadruped Robots by Skill Graph

Developing robotic intelligent systems that can adapt quickly to unseen wild situations is one of the critical challenges in pursuing autonomous robotics. Although some impressive progress has been made in walking stability and skill learning in the field of legged robots, their ability to fast adaptation is still inferior to that of animals in nature. Animals are born with massive skills needed to survive, and can quickly acquire new ones, by composing fundamental skills with limited experience. Inspired by this, we propose a novel framework, named Robot Skill Graph (RSG) for organizing massive fundamental skills of robots and dexterously reusing them for fast adaptation. Bearing a structure similar to the Knowledge Graph (KG), RSG is composed of massive dynamic behavioral skills instead of static knowledge in KG and enables discovering implicit relations that exist in be-tween of learning context and acquired skills of robots, serving as a starting point for understanding subtle patterns existing in robots' skill learning. Extensive experimental results demonstrate that RSG can provide rational skill inference upon new tasks and environments and enable quadruped robots to adapt to new scenarios and learn new skills rapidly

What influenced the lesion patterns and hemodynamic characteristics in patients with internal carotid artery stenosis? A retrospective study

•Blood perfusion influences ischemic lesions in patients with of ICAS.•Communicating arteries influence intracranial blood flow.•TCD was a convenient and rapid tool to assess cerebral blood flow

Mutation Status and Immunohistochemical Correlation of KRAS, NRAS, and BRAF in 260 Chinese Colorectal and Gastric Cancers

KRAS, NRAS and BRAF are kinases involved in the RAS-RAF-MAPK signaling pathway and also potential tumor-driven genes. Patients with KRAS/NRAS/BRAF mutations are resistant to anti-EGFR monoclonal antibody therapy. The main purpose of this study is to investigate the mutation status and distribution of KRAS/NRAS/BRAF in Chinese colorectal and gastric cancers, and to explore the histopathological changes and related immunohistochemical marker changes caused by these mutations. The mutation status of KRAS (exons 2, codon 12/13), NRAS (exons 2/3/4, codon 12/13/59/61/117/146) and BRAF (exons 15, codon 600) were detected by amplification refractory mutation system polymerase chain reaction (ARMS-PCR) in 86 colon cancer, 140 rectal cancer and 34 gastric cancer tissues. Then, the frequencies and distribution of KRAS/NRAS/BRAF mutations were described in detail. Furthermore, the relationship between KRAS/NRAS/BRAF mutations and the features of histopathological and related immunohistochemical markers were analyzed. The results showed that KRAS/NRAS/BRAF mutation rates in colon cancer were 44.2, 1.2, and 3.5%; in rectal cancer were 37.1, 4.3, and 0.7%; in gastric cancer were none, none and 2.9%. The mutation rate of KRAS in female (48.8%) is significantly higher than that of male (27.8%), and the mutation rate increased with the higher degree of differentiation. Additionally, the mutation rate of BRAF detected by ARMS-PCR (1.77%) was significantly lower than that by immunohistochemistry (4.11%). It also showed that the KRAS/NRAS/BRAF mutation status had a certain relationship with the expression of some immunohistochemical markers. This study provides more data support for clinical research on KRAS/NRAS/BRAF mutation in CRCs or gastric cancers

Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer