Clinical and Imaging Features of Primary Cardiac Angiosarcoma

This study aims to explore computed tomography (CT) and magnetic resonance imaging (MRI) features of patients diagnosed with primary cardiac angiosarcoma. The study involved the analysis of 12 patients diagnosed with primary cardiac angiosarcoma who underwent non-contrast (8/12) or contrast-enhanced CT (10/12) or MRI (4/12). Imaging appearances, including the tumor location and adjacent infiltration, were analyzed. All 12 lesions were located in the right atrium with a broad base. Adjacent invasion including the tricuspid valve and right ventricle (2/12), inferior or superior vena cava (2/12), pericardium (10/12), and right coronary artery (7/12) was common. On unenhanced CT scans, tumors in two patients were homogeneous in density, whereas the others were inhomogeneous. Ten patients showed heterogeneous enhancement. The enhancement pattern showed no direct correlation with the di erentiation degree of the tumor. Four lesions manifested as heterogeneous intensity, with hyperintense hemorrhage foci on both T1- and T2-weighted MRI. Three showed rim enhancement and one showed patchy enhancement. Primary cardiac angiosarcoma often involves the right side of the heart with infiltration of peripheral structures. CT features include typical inhomogeneous density on unenhanced scans and heterogeneous centripetal enhancement on enhanced scans. A cauliflower-like appearance on both T1- and T2-weighted MRI is common. The characteristic enhancement pattern of MRI remains to be determine

On the selection and design of proteins and peptide derivatives for the production of photoluminescent, red-emitting gold quantum clusters

Novel pathways of the synthesis of photoluminescent gold quantum clusters (AuQCs) using biomolecules as reactants provide biocompatible products for biological imaging techniques. In order to rationalize the rules for the preparation of red-emitting AuQCs in aqueous phase using proteins or peptides, the role of different organic structural units was investigated. Three systems were studied: proteins, peptides, and amino acid mixtures, respectively. We have found that cysteine and tyrosine are indispensable residues. The SH/S-S ratio in a single molecule is not a critical factor in the synthesis, but on the other hand, the stoichiometry of cysteine residues and the gold precursor is crucial. These observations indicate the importance of proper chemical behavior of all species in a wide size range extending from the atomic distances (in the AuI-S semi ring) to nanometer distances covering the larger sizes of proteins assuring the hierarchical structure of the whole self-assembled system

Benchmark analysis for robustness of multi-scale urban road networks under global disruptions

To date immunity to disruptions of multi-scale urban road networks (URNs) has not been effectively quantified. This study uses robustness as a meaningful - if partial - representation of immunity. We propose a novel Relative Area Index (RAI) based on traffic assignment theory to quantitatively measure the robustness of URNs under global capacity degradation due to three different types of disruptions, which takes into account many realistic characteristics. We also compare the RAI with weighted betweenness centrality, a traditional topological metric of robustness. We employ six realistic URNs as case studies for this comparison. Our analysis shows that RAI is a more effective measure of the robustness of URNs when multi-scale URNs suffer from global disruptions. This improved effectiveness is achieved because of RAI's ability to capture the effects of realistic network characteristics such as network topology, flow patterns, link capacity, and travel demand. Also, the results highlight the importance of central management when URNs suffer from disruptions. Our novel method may provide a benchmark tool for comparing robustness of multi-scale URNs, which facilitates the understanding and improvement of network robustness for the planning and management of URNs

CP asymmetry in B \to phi K_S in a SUSY SO(10) GUT

We study the $B\to \phi K_S$ decay in a SUSY SO(10) GUT. We calculate the mass spectrum of sparticles for a given set of parameters at the GUT scale. We complete the calculations of the Wilson coefficients of operators including the new operators which are induced by NHB penguins at LO using the MIA with double insertions. It is shown that the recent experimental results on the time-dependent CP asymmetry $S_{\phi K}$ in $B\to \phi K_S$, which is negative and can not be explained in SM, can be explained in the model where there are flavor non-diagonal right-handed down squark mass matrix elements of 2nd and 3rd generations whose size satisfies all relevant constraints from known experiments ($\tau \to \mu \gamma$, $B\to X_S\gamma, B_s\to \mu^+\mu^-, B\to X_s \mu^+\mu^-, B\to X_s g, \Delta M_s$, etc.). At the same time, the branching ratio for the decay can also be in agreement with experimental measurements.Comment: 14 pages, 4 figure

The DArk Matter Particle Explorer mission

The DArk Matter Particle Explorer (DAMPE), one of the four scientific space science missions within the framework of the Strategic Pioneer Program on Space Science of the Chinese Academy of Sciences, is a general purpose high energy cosmic-ray and gamma-ray observatory, which was successfully launched on December 17th, 2015 from the Jiuquan Satellite Launch Center. The DAMPE scientific objectives include the study of galactic cosmic rays up to $\sim 10$ TeV and hundreds of TeV for electrons/gammas and nuclei respectively, and the search for dark matter signatures in their spectra. In this paper we illustrate the layout of the DAMPE instrument, and discuss the results of beam tests and calibrations performed on ground. Finally we present the expected performance in space and give an overview of the mission key scientific goals.Comment: 45 pages, including 29 figures and 6 tables. Published in Astropart. Phy

Direct detection of a break in the teraelectronvolt cosmic-ray spectrum of electrons and positrons

High energy cosmic ray electrons plus positrons (CREs), which lose energy quickly during their propagation, provide an ideal probe of Galactic high-energy processes and may enable the observation of phenomena such as dark-matter particle annihilation or decay. The CRE spectrum has been directly measured up to $\sim 2$ TeV in previous balloon- or space-borne experiments, and indirectly up to $\sim 5$ TeV by ground-based Cherenkov $\gamma$-ray telescope arrays. Evidence for a spectral break in the TeV energy range has been provided by indirect measurements of H.E.S.S., although the results were qualified by sizeable systematic uncertainties. Here we report a direct measurement of CREs in the energy range $25~{\rm GeV}-4.6~{\rm TeV}$ by the DArk Matter Particle Explorer (DAMPE) with unprecedentedly high energy resolution and low background. The majority of the spectrum can be properly fitted by a smoothly broken power-law model rather than a single power-law model. The direct detection of a spectral break at $E \sim0.9$ TeV confirms the evidence found by H.E.S.S., clarifies the behavior of the CRE spectrum at energies above 1 TeV and sheds light on the physical origin of the sub-TeV CREs.Comment: 18 pages, 6 figures, Nature in press, doi:10.1038/nature2447

Platinum Integrated Graphene for Methanol Fuel Cells

Uniform and porous graphene nanoflake films (GNFs) have been investigated as a support for catalytic Pt nanoclusters in direct methanol electro-oxidation. Pt nanoclusters of varying thickness are deposited on GNFs using magnetron sputtering, and their effects on the electrocatalytic activity for oxidizing methanol are systemically studied. GNF supported Pt nanoclusters with ultralow catalyst loading exhibit high performance for methanol electrocatalytic oxidation with a large mass-specific peak current density and a ratio of forward to backward peak currents up to 1.4. These characteristics compare favorably to the majority of Pt−C based electrodes, except for those of carbon nanotubes with Pt decoration on both the inner and the outer wall surfaces. The results obtained are ascribed to a highly coupled network made of high-density 2−4 nm Pt monolayer nanoclusters on both the basal and edge planes of each nanoflakes of graphene. GNFs are a promising support material for developing next-generation advanced Pt based fuel cells and their relevant electrodes in the field of energy

CP violation in Bd,s→l+l−B_{d,s} \to l^+l^- in the model III 2HDM

We have calculated the Wilson coefficients $C_{10}, C_{Q_i}$ (i=1,2) in the $\bar{MS}$ renormalization scheme in the model III 2HDM. Using the obtained Wilson coefficients, we have analyzed the CP violation in decays $B^0_q\to l^+l^-$ (q=d,s) in the model. The CP asymmetry, $A_{CP}$, depends on the parameters of models and $A_{CP}$ in $B_d\to l^+l^-$ can be as large as 40% and 35% for $l=\tau$ and $l=\mu$ respectively. It can reach 4% for $B^0_s$ decays. Because in SM CP violation is smaller than or equal to O($10^{-3}$) which is unobservably small, an observation of CP asymmetry in the decays $B^0_q \to l^+l^- (q=d,s)$ would unambiguously signal the existence of new physics.Comment: revtex4, 16 pages, 7 figure

Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems

Intelligent personal assistant systems with either text-based or voice-based conversational interfaces are becoming increasingly popular around the world. Retrieval-based conversation models have the advantages of returning fluent and informative responses. Most existing studies in this area are on open domain "chit-chat" conversations or task / transaction oriented conversations. More research is needed for information-seeking conversations. There is also a lack of modeling external knowledge beyond the dialog utterances among current conversational models. In this paper, we propose a learning framework on the top of deep neural matching networks that leverages external knowledge for response ranking in information-seeking conversation systems. We incorporate external knowledge into deep neural models with pseudo-relevance feedback and QA correspondence knowledge distillation. Extensive experiments with three information-seeking conversation data sets including both open benchmarks and commercial data show that, our methods outperform various baseline methods including several deep text matching models and the state-of-the-art method on response selection in multi-turn conversations. We also perform analysis over different response types, model variations and ranking examples. Our models and research findings provide new insights on how to utilize external knowledge with deep neural models for response selection and have implications for the design of the next generation of information-seeking conversation systems.Comment: Accepted by the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, U.S.A. July 8-12, 2018 (Full Oral Paper