Modeling the Light Curves of the Luminous Type Ic Supernova 2007D

SN 2007D is a nearby (redshift z = 0.023146), luminous Type Ic supernova (SN) having a narrow light curve (LC) and high peak luminosity. Previous research based on the assumption that it was powered by the 56Ni cascade decay suggested that the inferred 56Ni mass and the ejecta mass are ~1.5 M ⊙ and ~3.5 M ⊙, respectively. In this paper, we employ some multiband LC models to model the R-band LC and the color (V − R) evolution of SN 2007D to investigate the possible energy sources powering them. We find that the pure 56Ni model is disfavored; the multiband LCs of SN 2007D can be reproduced by a magnetar whose initial rotational period P 0 and magnetic field strength B p are (or ) ms and (or ) G, respectively. By comparing the spectrum of SN 2007D with that of some superluminous SNe (SLSNe), we find that it might be a luminous SN like several luminous gap-filler optical transients that bridge ordinary and SLSNe, rather than a genuine SLSN

Modeling the Light Curves of the Luminous Type Ic Supernova 2007D

SN~2007D is a nearby (redshift $z = 0.023146$), luminous Type Ic supernova (SN) having a narrow light curve (LC) and high peak luminosity. Previous research based on the assumption that it was powered by the $^{56}$Ni cascade decay suggested that the inferred $^{56}$Ni mass and the ejecta mass are $\sim 1.5$M$_{\odot}$ and $\sim 3.5$M$_{\odot}$, respectively. In this paper, we employ some multiband LC models to model the $R$-band LC and the color ($V-R$) evolution of SN~2007D to investigate the possible energy sources powering them. We find that the pure $^{56}$Ni model is disfavored; the multiband LCs of SN~2007D can be reproduced by a magnetar whose initial rotational period $P_{0}$ and magnetic field strength $B_p$ are $7.28_{-0.21}^{+0.21}$ (or $9.00_{-0.42}^{+0.32}$) ms and $3.10_{-0.35}^{+0.36}\times 10^{14}$ (or $2.81_{-0.44}^{+0.43}\times 10^{14}$) G, respectively. By comparing the spectrum of SN~2007D with that of some superluminous SNe (SLSNe), we find that it might be a luminous SN like several luminous ``gap-filler" optical transients that bridge ordinary and SLSNe, rather than a genuine SLSN.Comment: 11 pages, 5 figures, 1 table, accepted for publication in Ap

GRB 120729A: External Shock Origin for Both the Prompt Gamma-Ray Emission and Afterglow

Gamma-ray burst (GRB) 120729A was detected by Swift/BAT and Fermi/GBM, and then rapidly observed by Swift/XRT, Swift/UVOT, and ground-based telescopes. It had a single long and smooth \gamma-ray emission pulse, which extends continuously to the X-rays. We report Lick/KAIT observations of the source, and make temporal and spectral joint fits of the multiwavelength light curves of GRB 120729A. It exhibits achromatic light-curve behavior, consistent with the predictions of the external shock model. The light curves are decomposed into four typical phases: onset bump (Phase I), normal decay (Phase II), shallow decay (Phase III), and post-jet break (Phase IV). The spectral energy distribution (SED) evolves from prompt \gamma-ray emission to the afterglow with photon index from Γγ=1.36 to Γ≈1.75. There is no obvious evolution of the SED during the afterglow. ...(Please see article full tet for complete abstract.

Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients

Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene-expression, grey matter volume (GMV) and the Positive and Negative Syndrome Scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia

Organic-Inorganic Perovskite Light-Emitting Electrochemical Cells with a Large Capacitance

While perovskite light-emitting diodes typically made with high work function anodes and low work function cathodes have recently gained intense interests. Perovskite light-emitting devices with two high work function electrodes with interesting features are demonstrated here. Firstly, electroluminescence can be easily obtained from both forward and reverse biases. Secondly, the results of impedance spectroscopy indicate that the ionic conductivity in the iodide perovskite (CH3 NH3PbI3) is large with a value of approximate to 10(-8) S cm(-1). Thirdly, the shift of the emission spectrum in the mixed halide perovskite (CH3NH3PbI3-Br-x(x)) light-emitting devices indicates that I(-)ions are mobile in the perovskites. Fourthly, this work shows that the accumulated ions at the interfaces result in a large capacitance (approximate to 100 mu F cm(-2)). The above results conclusively prove that the organic-inorganic halide perovskites are solid electrolytes with mixed ionic and electronic conductivity and the light-emitting device is a light-emitting electrochemical cell. The work also suggests that the organic-inorganic halide perovskites are potential energy-storage materials, which may be applicable in the field of solid-state supercapacitors and batteries.While perovskite light-emitting diodes typically made with high work function anodes and low work function cathodes have recently gained intense interests. Perovskite light-emitting devices with two high work function electrodes with interesting features are demonstrated here. Firstly, electroluminescence can be easily obtained from both forward and reverse biases. Secondly, the results of impedance spectroscopy indicate that the ionic conductivity in the iodide perovskite (CH3NH3PbI3) is large with a value of ≈10-8 S cm-1. Thirdly, the shift of the emission spectrum in the mixed halide perovskite (CH3NH3PbI3-xBrx) light-emitting devices indicates that I- ions are mobile in the perovskites. Fourthly, this work shows that the accumulated ions at the interfaces result in a large capacitance (≈100 μF cm-2). The above results conclusively prove that the organic-inorganic halide perovskites are solid electrolytes with mixed ionic and electronic conductivity and the light-emitting device is a light-emitting electrochemical cell. The work also suggests that the organic-inorganic halide perovskites are potential energy-storage materials, which may be applicable in the field of solid-state supercapacitors and batteries. Light-emitting electrochemical cells (LECs) of organic-inorganic perovskite (CH3NH3PbI3) with two high work function electrodes are demonstrated. Results indicate that CH3NH3PbI3 has an ionic conductivity of ≈10-8 S cm-1. The accumulated ions at the interfaces result in a large capacitance, which suggests a potential application in electrochemical energy-storage devices, such as solid-state supercapacitors and batteries

A model-based approach to assess reproducibility for large-scale high-throughput MRI-based studies

Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies

Magnetic SERS-based immunoassay for cancer biomarker detection

Cancer is the world's second leading cause of death despite exponential growth in the knowledge of cancer and technological advancement in the area of cancer research over the last two decades. This is commonly attributed by dietary risks, lifestyle factor, late-stage presentation and late detection. Early detection of cancer at early stage is essential for preventing the development of cancer into advance stage and it increase the patient‟s chance for successful treatment. Herein, we developed a magnetic SERS-based immunoassay for fast and sensitive liquid biopsy of common human cancer biomarkers present in biofluids, e.g. prostate specific antigen (PSA), carcinoembryonic antigen (CEA) and Alpha-fetoprotein (AFP). The quantitative analysis was conducted by integrating the use of multifunctional magnetic nanochains and surface-enhanced Raman spectroscopy (SERS) technique. In the experiment, we made use of the self-polymerization property of musselinspired polydopamine (PDA) to fabricate functionalized chains of magnetic Fe3O4 nanoparticles as a straight forward and effective approach to capture and isolate target biomarkers. Gold nanorod (AuNR) based SERS probes were encoded with a unique Raman reporter molecule and is functionalized with highly-specific monoclonal antibody to detect the target cancer biomarkers. Consequently, in the presence of target biomarkers it will lead to the formation of magnetic chain/biomarker/SERS probe sandwich immunocomplexes that underwent SERS characterization. The quantitative analysis had revealed a consistent increase of SERS intensity with increasing concentration of cancer biomarkers and calibration curves had shown a substantial linearity (coefficient of determination, R2 > 0.966) throughout tested cancer biomarkers. Results suggest that this SERS-based immunoassay of liquid biopsy platform for detecting biomarkers has high potential for biosensing applications in medical diagnostics.Bachelor of Engineering (Chemical and Biomolecular Engineering

Extraction and imaging of aerodynamically generated sound field of rotor blades in the wind tunnel test

International audienc

Acoustical source reconstruction from non-synchronous sequential measurements by Fast Iterative Shrinkage Thresholding Algorithm

International audienceAcoustical source reconstruction is a typical inverse problem, whose minimum frequency of reconstruction hinges on the size of the array and maximum frequency depends on the spacing distance between the microphones. For the sake of enlarging the frequency of reconstruction and reducing the cost of an acquisition system, Cyclic Projection (CP), a method of sequential measurements without reference, was recently investigated (JSV,2016,372:31-49). In this paper, the Propagation based Fast Iterative Shrinkage Thresholding Algorithm (Propagation-FISTA) is introduced, which improves CP in two aspects: (1) the number of acoustic sources is no longer needed and the only making assumption is that of a “weakly sparse” eigenvalue spectrum; (2) the construction of the spatial basis is much easier and adaptive to practical scenarios of acoustical measurements benefiting from the introduction of propagation based spatial basis. The proposed Propagation-FISTA is first investigated with different simulations and experimental setups and is next illustrated with an industrial case