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Abstract Precise fundamental atmospheric stellar parameters and abundance determination of individual elements in stars are important for all stellar population studies. Non–local thermodynamic equilibrium (non-LTE; hereafter NLTE) models are often important for such high precision, however, can be computationally complex and expensive, which renders the models less utilized in spectroscopic analyses. To alleviate the computational burden of such models, we developed a robust 1D, NLTE fundamental atmospheric stellar parameter derivation tool, LOTUS , to determine the effective temperature T eff , surface gravity log g , metallicity [Fe/H], and microturbulent velocity v mic for FGK-type stars, from equivalent width (EW) measurements of Fe i and Fe ii lines. We utilize a generalized curve of growth method to take into account the EW dependencies of each Fe i and Fe ii line on the corresponding atmospheric stellar parameters. A global differential evolution optimization algorithm is then used to derive the fundamental parameters. Additionally, LOTUS can determine precise uncertainties for each stellar parameter using a Markov Chain Monte Carlo algorithm. We test and apply LOTUS on a sample of benchmark stars, as well as stars with available asteroseismic surface gravities from the K2 survey, and metal-poor stars from the Gaia-ESO and R -Process Alliance surveys. We find very good agreement between our NLTE-derived parameters in LOTUS to nonspectroscopic values on average within T eff = ±30 K, and log g = ±0.10 dex for benchmark stars. We provide open access of our code, as well as of the interpolated precomputed NLTE EW grids available on Github (the software is available on GitHub 3 3 https://github.com/Li-Yangyang/LOTUS under an MIT License, and version 0.1.1 (as the persistent version) is archived in Zenodo) and documentation with working examples on the Readthedocs book. 

Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package. 

In this study, we analyzed the optical observations of a subluminous Type Ia supernova (SN Ia) 2017fzw, which exhibited high photospheric velocity (HV) at B-band maximum light. The absolute B-band peak magnitude was determined to be MmaxB=−18.65±0.13 mag, similar to 91bg-like SNe Ia. An estimation of the rate of decline for the B-band light curve was determined to be Δm15(B)=1.60±0.06 mag. The spectra of SN 2017fzw were similar to those of 91bg-like SNe Ia, with prominent Ti ii and Si ii λ5972 features at early phases, gradually transitioning to spectra resembling normal (mainly HV subclass) SNe Ia at later phases, with a stronger Ca ii NIR feature. Notably, throughout all phases of observation, SN 2017fzw displayed spectral evolution characteristics that were comparable to those of HV SNe Ia, and at peak brightness, the Si ii λ6355 velocity was determined to be 13,800 ± 415 km s−1 and a more pronounced Ca ii NIR feature was also detected. Based on these findings, we classify SN 2017fzw as a transitional object with properties of both normal and 91bg-like SNe Ia, providing support for the hypothesis of a continuous distribution of supernovae between these two groups.

 

We present a comparative study of two nearby type Ia supernovae (SNe Ia), 2018xx and 2019gbx, that exploded in NGC 4767 and MCG-02-33-017 at a distance of 48 Mpc and 60 Mpc, respectively. The B -band light curve decline rate for SN 2018xx is estimated to be 1.48 ± 0.07 mag and for SN 2019gbx it is 1.37 ± 0.07 mag. Despite the similarities in photometric evolution, quasi-bolometric luminosity, and spectroscopy between these two SNe Ia, SN 2018xx has been found to be fainter by about ∼0.38 mag in the B -band and has a lower 56 Ni yield. Their host galaxies have similar metallicities at the SN location, indicating that the differences between these two SNe Ia may be associated with the higher progenitor metallicity of SN 2018xx. Further inspection of the near-maximum-light spectra has revealed that SN 2018xx has relatively strong absorption features near 4300 Å relative to SN 2019gbx. The application of the code TARDIS fitting to the above features indicates that the absorption features near 4300 Å appear to be related to not only Fe  II /Mg  II abundance but possibly to the other element abundances as well. Moreover, SN 2018xx shows a weaker carbon absorption at earlier times, which is also consistent with higher ejecta metallicity. 

Owing to its great threat to human health and environment, Pb²⁺pollution has been recognized as a major public problem by the World Health Organization (WHO). Many DNA aptamers have been utilized in the development of Pb²⁺-detection sensors, but the underlying mechanisms remain elusive. Here, we report three Pb²⁺-complexed structures of the thrombin binding aptamer (TBA). These high-resolution crystal structures showed that TBA forms intramolecular G-quadruplex and Pb²⁺is bound by the two G-tetrads in the center. Compared to K⁺-stabilized G-quadruplexes, the coordinating distance between Pb²⁺and the G-tetrads are much shorter. The T3T4 and T12T13 linkers play important roles in dimerization and crystallization of TBA, but they are changeable for Pb²⁺-binding. In combination with mutagenesis and CD spectra, the G8C mutant structure unraveled that the T7G8T9 linker of TBA is also variable. In addition to expansion of the Pb²⁺-binding aptamer sequences, our study also set up one great example for quick and rational development of other aptamers with similar or optimized binding activity.

 

Elucidation of complex molecular networks requires integrative analysis of molecular features and changes at different levels of information flow and regulation. Accordingly, high throughput functional genomics tools such as transcriptomics, proteomics, metabolomics, and lipidomics have emerged to provide system-wide investigations. Unfortunately, analysis of different types of biomolecules requires specific sample extraction procedures in combination with specific analytical instrumentation. The most efficient extraction protocols often only cover a restricted type of biomolecules due to their different physicochemical properties. Therefore, several sets/aliquots of samples are needed for extracting different molecules. Here we adapted a biphasic fractionation method to extract proteins, metabolites, and lipids from the same sample (3-in-1) for liquid chromatography-tandem mass spectrometry (LC-MS/MS) multi-omics. To demonstrate utility of the improved method, we used bacteria-primed Arabidopsis leaves to generate multi-omics datasets from the same sample. In total, we were able to analyze 1849 proteins, 1967 metabolites, and 424 lipid species in single samples. The molecules cover a wide range of biological and molecular processes, and allow quantitative analyses of different molecules and pathways. Our results have shown the clear advantages of the multi-omics method, including sample conservation, high reproducibility, and tight correlation between different types of biomolecules. 

Charge trapping degrades the energy resolution of germanium (Ge) detectors, which require to have increased experimental sensitivity in searching for dark matter and neutrinoless double-beta decay. We investigate the charge trapping processes utilizing nine planar detectors fabricated from USD-grown crystals with well-known net impurity levels. The charge collection efficiency as a function of charge trapping length is derived from the Shockley-Ramo theorem. Furthermore, we develop a model that correlates the energy resolution with the charge collection efficiency. This model is then applied to the experimental data. As a result, charge collection efficiency and charge trapping length are determined accordingly. Utilizing the Lax model (further developed by CDMS collaborators), the absolute impurity levels are determined for nine detectors. The knowledge of these parameters when combined with other traits such as the Fano factor serve as a reliable indicator of the intrinsic nature of charge trapping within the crystals. We demonstrate that electron trapping is more severe than hole trapping in a p-type detector and the charge collection efficiency depends on the absolute impurity level of the Ge crystal when an adequate bias voltage is applied to the detector. Negligible charge trapping is found when the absolute impurity level is less than 1.0$\times$10$^11/^3$ for collecting electrons and 2.0$\times$10$^11/^3$ for collecting holes.