A kilonova associated with GRB 070809

For on-axis typical short gamma-ray bursts (sGRBs), the forward shock emission is usually so bright that renders the identification of kilonovae (also known as macronovae) in the early afterglow ($t<0.5$ d) phase rather challenging. This is why previously no thermal-like kilonova component has been identified at such early time except in the off-axis dim GRB 170817A associated with GW170817. Here we report the identification of an unusual optical radiation component in GRB 070809 at $t\sim 0.47$ d, thanks plausibly to the very-weak/subdominant forward shock emission. The optical emission with a very red spectrum is well in excess of the extrapolation of the X-ray emission that is distinguished by an unusually hard spectrum, which is at odds with the forward shock afterglow prediction but can be naturally interpreted as a kilonova. Our finding supports the speculation that kilonovae are ubiquitous , and demonstrates the possibility of revealing the neutron star merger origin with the early afterglow data of some typical sGRBs that take place well beyond the sensitive radius of the advanced gravitational wave detectors and hence the opportunity of organizing dedicated follow-up observations for events of interest.Comment: 20 pages, 5 figures, published in Nature Astronom

Electronic Structures and Optical Properties of Phenyl C 71

Phenyl C71 butyric acid methyl ester (PC71BM) has been adopted as electron acceptor materials in bulk heterojunction solar cells with relatively higher power conversion efficiency. The understanding of the mechanism and performance for the devices based upon PC71BM requires the information of conformations, electronic structures, optical properties, and so forth. Here, the geometries, IR and Raman, electronic structures, polarizabilities, and hyperpolarizabilities of PC71BM isomers are studied by using density functional theory (DFT); the absorption and excitation properties are investigated via time-dependent DFT with B3LYP, PBE0, and CAM-B3LYP functionals. The calculated results show that [6,6]PC71BM is more stable than [5,6]PC71BM due to the lower total energy. The vibrational modes of the isomers at IR and Raman peaks are quite similar. As to absorption properties, CAM-B3LYP functional is the suitable functional for describing the excitations of PC71BM because the calculated results with CAM-B3LYP functional agree well with that of the experiment. The analysis of transition configurations and molecular orbitals demonstrated that the transitions at the absorption maxima in UV/Vis region are localized π-π* transitions in fullerenes cages. Furthermore, the larger isotropic polarizability of PC71BM indicates that the response of PC71BM to applied external electric field is stronger than that of PC61BM, and therefore resulting into better nonlinear optical properties

Pd nanocrystals with continuously tunable high-index facets as a model nanocatalyst

Knowledge of the structure–reactivity relationship of catalysts is usually gained through using well-defined bulk single-crystal planes as model catalysts. However, there exists a huge gap between bulk single-crystal planes and practical nanocatalysts in terms of size, structural complexity, and local environment. Herein, we efficiently bridged this gap by developing a model nanocatalyst based on nanocrystals with continuously tunable surface structures. Pd nanocrystals with finely tunable facets, ranging from a flat {100} low-index facet to a series of {hk0} high-index facets, were prepared by an electrochemical square-wave potential method. The validity of the Pd model nanocatalyst has been demonstrated by structure–reactivity studies of electrocatalytic oxidation of small organic molecules. We further observed that Pd nanocrystals exhibited catalytic performance considerably different from bulk Pd single-crystal planes with the same Miller indices. Such differences were attributed to special catalytic functions conferred by nanocrystal edges. This study paves a promising route for investigating catalytic reactions effectively at the atomic level and nanoscales

Mesaconine alleviates doxorubicin-triggered cardiotoxicity and heart failure by activating PINK1-dependent cardiac mitophagy

Aberrant mitophagy has been identified as a driver for energy metabolism disorder in most cardiac pathological processes. However, finding effective targeted agents and uncovering their precise modulatory mechanisms remain unconquered. Fuzi, the lateral roots of Aconitum carmichaelii, shows unique efficacy in reviving Yang for resuscitation, which has been widely used in clinics. As a main cardiotonic component of Fuzi, mesaconine has been proven effective in various cardiomyopathy models. Here, we aimed to define a previously unrevealed cardioprotective mechanism of mesaconine-mediated restoration of obstructive mitophagy. The functional implications of mesaconine were evaluated in doxorubicin (DOX)-induced heart failure models. DOX-treated mice showed characteristic cardiac dysfunction, ectopic myocardial energy disorder, and impaired mitophagy in cardiomyocytes, which could be remarkably reversed by mesaconine. The cardioprotective effect of mesaconine was primarily attributed to its ability to promote the restoration of mitophagy in cardiomyocytes, as evidenced by elevated expression of PINK1, a key mediator of mitophagy induction. Silencing PINK1 or deactivating mitophagy could completely abolish the protective effects of mesaconine. Together, our findings suggest that the cardioprotective effects of mesaconine appear to be dependent on the activation of PINK1-induced mitophagy and that mesaconine may constitute a promising therapeutic agent for the treatment of heart failure

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelize an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish