Chiral capillary electrophoresis-mass spectrometry: developments and applications of novel glucopyranosdie molecular micelles

Micellar electrokinetic chromatography (MEKC), one of the major capillary electrophoresis (CE) modes, has been interfaced to mass spectrometry (MS) to provide high sensitivity and selectivity for analysis of chiral compounds. The research in this dissertation presents the development of novel polymeric glucopyranoside based molecular micelles (MoMs) (aka. polymeric surfactants) and their application in chiral MEKC-MS. Chapter 1 is a review of chiral CE-MS - in the period 2010-2015. In this chapter, the fundamental of chiral CE and CE-MS is illustrated and the recent developments of chiral selectors and their applications in chiral EKC-MS, CEC-MS and MEKC-MS are discussed in details. Chapter 2 introduces the development of a novel polymeric α-D-glucopyranoside based surfactants, n-alkyl-α-D-glucopyranoside 4,6-hydrogen phosphate, sodium salt. In this chapter, polymeric α-D-glucopyranoside-based surfactants with different chain length and head groups have been successfully synthesized, characterized and applied as compatible chiral selector in MEKC-ESI-MS/MS. or the enantioseparation of ephedrines and β-blockers. Chapter 3 continues to describe the employment of polymeric glucopyranoside based surfactants as chiral selector in MEKC-MS/MS. The polymeric β-D-glucopyranoside based surfactants, containing charged head groups such as n-alkyl β-D-glucopyranoside 4,6-hydrogen phosphate, sodium salt and n-alkyl β-D-glucopyranoside 6-hydrogen sulfate, monosodium salt were able to enantioseparate 21 cationic drugs and 8 binaphthyl atropisomers (BAIs) in MEKC-MS/MS, which promises to open up the possibility of turning an analytical technique into high throughput screening of chiral compounds. Physicochemical properties and enantioseparation capability of polymeric β-D-glucopyranoside based surfactants with different head groups and chain lengths were compared. Moreover, the comparison of polymeric α- and β-D-glucopyranoside 4,6-hydrogen phosphate, sodium salt were further explored with regard to enantioseparations of ephedrine alkaloids and b-blockers. The concept of multiplex chiral MEKC-MS for high throughput quantitation is demonstrated for the first time in scientific literature

Distinct Surface and Bulk Thermal Behaviors of LiNi0.6Mn0.2Co0.2O2 Cathode Materials as a Function of State of Charge.

Understanding how structural and chemical transformations take place in particles under thermal conditions can inform designing thermally robust electrode materials. Such a study necessitates the use of diagnostic techniques that are capable of probing the transformations at multiple length scales and at different states of charge (SOC). In this study, the thermal behavior of LiNi0.6Mn0.2Co0.2O2 (NMC-622) was examined as a function of SOC, using an array of bulk and surface-sensitive techniques. In general, thermal stability decreases as lithium content is lowered and conversion in the bulk to progressively reduced metal oxides (spinels, rock salt) occurs as the temperature is raised. Hard X-ray absorption spectroscopy (XAS) and X-ray Raman spectroscopy (XRS) experiments, which probe the bulk, reveal that Ni and Co are eventually reduced when partially delithiated samples (regardless of the SOC) are heated, although Mn is not. Surface-sensitive synchrotron techniques, such as soft XAS and transmission X-ray microscopy (TXM), however, reveal that for 50% delithiated samples, apparent oxidation of nickel occurs at particle surfaces under some circumstances. This is partially compensated by reduction of cobalt but may also be a consequence of redistribution of lithium ions upon heating. TXM results indicate the movement of reduced nickel ions into particle interiors or oxidized nickel ions to the surface or both. These experiments illustrate the complexity of the thermal behavior of NMC cathode materials. The study also informs the importance of investigating the surface and bulk difference as a function of SOC when studying the thermal behaviors of battery materials

Neuropeptide F regulates courtship in Drosophila through a male-specific neuronal circuit.

Male courtship is provoked by perception of a potential mate. In addition, the likelihood and intensity of courtship are influenced by recent mating experience, which affects sexual drive. Using Drosophila melanogaster, we found that the homolog of mammalian neuropeptide Y, neuropeptide F (NPF), and a cluster of male-specific NPF (NPFM) neurons, regulate courtship through affecting courtship drive. Disrupting NPF signaling produces sexually hyperactive males, which are resistant to sexual satiation, and whose courtship is triggered by sub-optimal stimuli. We found that NPFM neurons make synaptic connections with P1 neurons, which comprise the courtship decision center. Activation of P1 neurons elevates NPFM neuronal activity, which then act through NPF receptor neurons to suppress male courtship, and maintain the proper level of male courtship drive

Faster Depth-Adaptive Transformers

Depth-adaptive neural networks can dynamically adjust depths according to the hardness of input words, and thus improve efficiency. The main challenge is how to measure such hardness and decide the required depths (i.e., layers) to conduct. Previous works generally build a halting unit to decide whether the computation should continue or stop at each layer. As there is no specific supervision of depth selection, the halting unit may be under-optimized and inaccurate, which results in suboptimal and unstable performance when modeling sentences. In this paper, we get rid of the halting unit and estimate the required depths in advance, which yields a faster depth-adaptive model. Specifically, two approaches are proposed to explicitly measure the hardness of input words and estimate corresponding adaptive depth, namely 1) mutual information (MI) based estimation and 2) reconstruction loss based estimation. We conduct experiments on the text classification task with 24 datasets in various sizes and domains. Results confirm that our approaches can speed up the vanilla Transformer (up to 7x) while preserving high accuracy. Moreover, efficiency and robustness are significantly improved when compared with other depth-adaptive approaches.Comment: AAAI-2021. Code will appear at: https://github.com/Adaxry/Adaptive-Transforme