Articles you may be interested inDynamics of the reactions of O(1D) with CD3OH and CH3OD studied with time-resolved Fourier-transform IR spectroscopy J. Chem. Phys. 137, 164307 (2012); 10.1063/1.4759619 Photolysis of n -butyl nitrite and isoamyl nitrite at 355 nm: A time-resolved Fourier transform infrared emission spectroscopy and ab initio study Terahertz time-domain studies of far-infrared dielectric response in 5 mol % MgO : LiNbO 3 ferroelectric single crystalThis letter describes the use of THz time-domain spectroscopy (TDS) applied in transmission to the secondary explosive 1,3,5 trinitro-s-triazine. Samples were also subjected to Fourier transform infrared spectroscopy over the same range for comparison. A detailed spectroscopy study is presented. General agreement between results from both methods confirms the absorption features found. A comparison study with computer molecular simulations shows that THz-TDS is sensitive to collective modes or vibrational modes of material.
92 Nb 1.5 O 6.92 ͑BZN͒ has been investigated by infrared spectroscopy. Spectra were collected from 30 to 3300 cm −1 between 50 and 300 K, and the optical constants were estimated by Kramers-Kronig analysis and classical dispersion theory. In addition, BZN was studied by terahertz techniques to lower frequencies. Infrared-active phonon modes have been assigned to specific bending and stretching vibrational modes. A previously unassigned infrared mode at ϳ850 cm −1 is discussed. A splitting of the B-O stretching phonon modes and O-B-O bending modes is assigned to mixed-cation occupancy. The temperature dependence of the phonon frequencies and the damping coefficients are consistent with a decrease of both lattice constant and orientational disorder at low temperatures.
Experimental studies of granular solids have shown that significant scattering effects restrict the accurate determination of material absorption in the terahertz (THz) region. The present work investigates the grain size dependent scattering contribution on the extinction spectra of Ammonium Nitrate, flour and salt between 0.2 to 1.2 THz using THz time-domain spectroscopy. The scattering contribution can be estimated by applying Mie theory for spherical grains. The approach essentially separates the independent contributions of true absorption and scattering losses and thus determines the total extinction for different grain sizes of various materials. The separation of the intrinsic material absorption from scattering losses shows that the frequency dependence in weakly absorbing materials is predominantly particle size dependent. Consequently, that range of THz frequencies cannot be used to differentiate granular solids having no intrinsic absorption.
Unravelling the regulatory programs from single-cell multi-omics data has long been one of the major challenges in genomics, especially in the current emerging single-cell field. Currently there is a huge gap between fast-growing single-cell multi-omics data and effective methods for the integrative analysis of these inherent sparse and heterogeneous data. In this study, we have developed a novel method, Single-cell Multi-omics Gene co-Regulatory algorithm (SMGR), to detect coherent functional regulatory signals and target genes from the joint single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data obtained from different samples. Given that scRNA-seq and scATAC-seq data can be captured by zero-inflated Negative Binomial distribution, we utilize a generalized linear regression model to identify the latent representation of consistently expressed genes and peaks, thus enables the identification of co-regulatory programs and the elucidation of regulating mechanisms. Results from both simulation and experimental data demonstrate that SMGR outperforms the existing methods with considerably improved accuracy. To illustrate the biological insights of SMGR, we apply SMGR to mixed-phenotype acute leukemia (MPAL) and identify the MPAL-specific regulatory program with significant peak-gene links, which greatly enhance our understanding of the regulatory mechanisms and potential targets of this complex tumor.
Noise in cellular systems is often modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), but the low efficiency of the SSA limits its application to large biochemical networks. To improve the efficiency of stochastic simulations, Haseltine and Rawlings (HR) proposed a hybrid algorithm, which combines ordinary differential equations for traditional deterministic models and the SSA for stochastic models. In this paper, accuracy of the HR hybrid method is studied based on a linear chain reaction system. Mathematical analysis and numerical results both show that the HR hybrid method is accurate if either the quantity of reactant molecules in fast reactions is above a certain threshold, or the reaction rates of fast reactions are much larger than those of slow reactions. This analysis also shows that the HR hybrid method approximates the chemical master equation well for a much greater region in system parameter space than the slow-scale SSA and the stochastic quasi-steady-state assumption methods.
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