Neutral and Cationic Organoantimony Compounds as Lewis Acid Catalysts

Organoantimony(V) compounds are potent Lewis acids which have been used for the complexation of anions or for the catalysis of organic reactions. Inspired by the broad range of applications developed for the stable Group 13 Lewis acid B(Cv6Fv5)v3, as well as the fact that SbFv5 is more acidic than BFv3, we set out to investigate organoantimony compounds in the context of Lewis acid catalysis. To this end, we synthesized electrophilic Sb(III) and Sb(V) complexes featuring electron-withdrawing halogenated ligands, cationic charges, and/or ancillary donor ligands, and tested these compounds in a number of organic transformations. Computational studies of their electronic structures provided us with insights into their unusual properties. We compared a series of triarylstibines with their tetrachlorocatecholate stiborane analogs, and demonstrated that the Lewis acidity of organoantimony(III) species can be readily enhanced by oxidation to the +V state, a phenomenon that is rationalized by the lowering of the antimony-based accepting Ó* orbital and a “deepening” of the associated Ó-hole upon oxidation. We also reported the synthesis of triarylfluoro- and triarylchloro- stibonium cations, among which the trimesitylchlorostibonium hexachloroantimonate is free from direct cation-anion interactions due to the steric shielding provided by the mesityl substituents. However, this cation is not as reactive as its phenyl derivative in the catalytic polymerization of THF and the Friedel-Craft dimerization of 1,1-diphenlyethylene. Additionally, we evaluated a series of tetraarylstibonium cations as catalysts for the cycloaddition of isocyanates to oxiranes. While all stibonium cations favor the 3,4-oxazolidinone products, the bulkier cations are found to be the most selective. Furthermore, we compared a series of ortho-phenylene based pnictogen cations and dications with their monofunctional derivatives as catalysts for the transfer hydrogenation of quinone derivatives with Hantzsch ester, and found that their catalytic reactivity follows the Lewis acidity trend in the order Sb dication > Sb monocation > P monocation. Lastly, this dissertation also investigates the electronic structures of selected organoantimony(V) compounds with the view to understand how coordination events at the antimony center affect the photophysical properties of these compounds

Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling

High-resolution (HR) images are usually downscaled to low-resolution (LR) ones for better display and afterward upscaled back to the original size to recover details. Recent work in image rescaling formulates downscaling and upscaling as a unified task and learns a bijective mapping between HR and LR via invertible networks. However, in real-world applications (e.g., social media), most images are compressed for transmission. Lossy compression will lead to irreversible information loss on LR images, hence damaging the inverse upscaling procedure and degrading the reconstruction accuracy. In this paper, we propose the Self-Asymmetric Invertible Network (SAIN) for compression-aware image rescaling. To tackle the distribution shift, we first develop an end-to-end asymmetric framework with two separate bijective mappings for high-quality and compressed LR images, respectively. Then, based on empirical analysis of this framework, we model the distribution of the lost information (including downscaling and compression) using isotropic Gaussian mixtures and propose the Enhanced Invertible Block to derive high-quality/compressed LR images in one forward pass. Besides, we design a set of losses to regularize the learned LR images and enhance the invertibility. Extensive experiments demonstrate the consistent improvements of SAIN across various image rescaling datasets in terms of both quantitative and qualitative evaluation under standard image compression formats (i.e., JPEG and WebP).Comment: Accepted by AAAI 2023. Code is available at https://github.com/yang-jin-hai/SAI

Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms

Blind watermarking provides powerful evidence for copyright protection, image authentication, and tampering identification. However, it remains a challenge to design a watermarking model with high imperceptibility and robustness against strong noise attacks. To resolve this issue, we present a framework Combining the Invertible and Non-invertible (CIN) mechanisms. The CIN is composed of the invertible part to achieve high imperceptibility and the non-invertible part to strengthen the robustness against strong noise attacks. For the invertible part, we develop a diffusion and extraction module (DEM) and a fusion and split module (FSM) to embed and extract watermarks symmetrically in an invertible way. For the non-invertible part, we introduce a non-invertible attention-based module (NIAM) and the noise-specific selection module (NSM) to solve the asymmetric extraction under a strong noise attack. Extensive experiments demonstrate that our framework outperforms the current state-of-the-art methods of imperceptibility and robustness significantly. Our framework can achieve an average of 99.99% accuracy and 67.66 dB PSNR under noise-free conditions, while 96.64% and 39.28 dB combined strong noise attacks. The code will be available in https://github.com/rmpku/CIN.Comment: 9 pages, 9 figures, 5 table

Neuromorphic computing using wavelength-division multiplexing

Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potential to dramatically enhance the computing power and energy efficiency of mainstream electronic processors, due to their ultralarge bandwidths of up to 10s of terahertz together with their analog architecture that avoids the need for reading and writing data back and forth. Different multiplexing techniques have been employed to demonstrate ONNs, amongst which wavelength division multiplexing (WDM) techniques make sufficient use of the unique advantages of optics in terms of broad bandwidths. Here, we review recent advances in WDM based ONNs, focusing on methods that use integrated microcombs to implement ONNs. We present results for human image processing using an optical convolution accelerator operating at 11 Tera operations per second. The open challenges and limitations of ONNs that need to be addressed for future applications are also discussed.Comment: 13 pages, 8 figures, 160 reference

Maximizing the performance for microcomb based microwave photonic transversal signal processors

Microwave photonic (MWP) transversal signal processors offer a compelling solution for realizing versatile high-speed information processing by combining the advantages of reconfigurable electrical digital signal processing and high-bandwidth photonic processing. With the capability of generating a number of discrete wavelengths from micro-scale resonators, optical microcombs are powerful multi-wavelength sources for implementing MWP transversal signal processors with significantly reduced size, power consumption, and complexity. By using microcomb-based MWP transversal signal processors, a diverse range of signal processing functions have been demonstrated recently. In this paper, we provide a detailed analysis for the processing inaccuracy that is induced by the imperfect response of experimental components. First, we investigate the errors arising from different sources including imperfections in the microcombs, the chirp of electro-optic modulators, chromatic dispersion of the dispersive module, shaping errors of the optical spectral shapers, and noise of the photodetector. Next, we provide a global picture quantifying the impact of different error sources on the overall system performance. Finally, we introduce feedback control to compensate the errors caused by experimental imperfections and achieve significantly improved accuracy. These results provide a guide for optimizing the accuracy of microcomb-based MWP transversal signal processors.Comment: 15 pages, 12 figures, 60 reference

Model simulations of the annual cycle of the landfast ice thickness in the East Siberian Sea

The annual cycle of the thickness and temperature of landfast sea ice in the East Siberian Sea has been examined using a one-dimensional thermodynamic model. The model was calibrated for the year August 2012–July 2013, forced using the data of the Russian weather station Kotel’ny Island and ECMWF reanalyses. Thermal growth and decay of ice were reproduced well, and the maximum annual ice thickness and breakup day became 1.64 m and the end of July. Oceanic heat flux was 2 W.m–2 in winter and raised to 25 W.m–2 in summer, albedo was 0.3–0.8 depending on the surface type (snow/ice and wet/dry). The model outcome showed sensitivity to the albedo, air temperature and oceanic heat flux. The modelled snow cover was less than 10 cm having a small influence on the ice thickness. In situ sea ice thickness in the East Siberian Sea is rarely available in publications. This study provides a method for quantitative ice thickness estimation by modelling. The result can be used as a proxy to understand the sea ice conditions on the Eurasian Arctic coast, which is important for shipping and high-resolution Arctic climate modelling

Financially insecure and less ethical: Understanding why and when financial insecurity inhibits ethical leadership

With the recent COVID-19 pandemic among other crises (e.g., Russia–Ukraine conflicts and recession projections) threatening organizations’ financial conditions across the globe, supervisors may not only encounter challenges such as job cuts that test their ethical leadership, but also experience financial insecurity themselves. However, our knowledge of why and when supervisors’ ethical leadership behaviors may be affected in such a situation remains quite limited. In this research, we draw on uncertainty management theory (UMT) to examine the potential influence of financial insecurity on ethical leadership. Specifically, we suggest that financial insecurity triggers anxiety in supervisors, which inhibits their demonstration of ethical leadership. We also propose organizational pay fairness as a boundary condition for this process, such that supervisors who perceive their pay as fair are less susceptible to the anxiety resulting from financial insecurity than those who perceive their pay as unfair. Results from two multi-source, multi-wave studies supported our hypothesized model. We conclude by discussing the theoretical and practical implications of our findings

Physiological dynamics as indicators of plant response to manganese binary effect

IntroductionHeavy metals negatively affect plant physiology. However, plants can reduce their toxicity through physiological responses. Broussonetia papyrifera is a suitable candidate tree for carrying out the phytoremediation of manganese (Mn)-contaminated soil.MethodsConsidering that Mn stress typically exerts a binary effect on plants, to reveal the dynamic characteristics of the physiological indexes of B. papyrifera to Mn stress, we conducted pot experiments with six different Mn concentrations (0, 0.25, 0.5, 1, 2, and 5 mmol/L) for 60 days. In addition to the chlorophyll content, malondialdehyde (MDA), proline (PRO), soluble sugar, superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), the absorption and transfer characteristics of Mn, and root structure were also measured.ResultsPhytoremedial potential parameters such as the bioconcentration factor (BCF) and translocation factor (TF) displayed an increasing trend with the increase of Mn concentration. At lower Mn concentrations (<0.5 mmol/L), the TF value was <1 but crossed 1 when the Mn concentration exceeded 100 mmol/L. The Mn distribution in various tissues was in the following order: leaf > stem > root. The root structure analysis revealed that low-level concentrations of Mn (1 mmol/L) promoted root development. Mn concentration and stress duration had significant effects on all measured physiological indexes, and except soluble sugar, Mn concentration and stress time displayed a significant interaction on the physiological indexes.DiscussionOur study demonstrates that the physiological indexes of B. papyrifera display dynamic characteristics under Mn stress. Thus, during the monitoring process of Mn stress, it appears to be necessary to appropriately select sampling parts according to Mn concentration

Neurometabolic and structural alterations of medial septum and hippocampal CA1 in a model of post-operative sleep fragmentation in aged mice: a study combining 1H-MRS and DTI

Post-operative sleep disturbance is a common feature of elderly surgical patients, and sleep fragmentation (SF) is closely related to post-operative cognitive dysfunction (POCD). SF is characterized by sleep interruption, increased number of awakenings and sleep structure destruction, similar to obstructive sleep apnea (OSA). Research shows that sleep interruption can change neurotransmitter metabolism and structural connectivity in sleep and cognitive brain regions, of which the medial septum and hippocampal CA1 are key brain regions connecting sleep and cognitive processes. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive method for the evaluation of neurometabolic abnormalities. Diffusion tensor imaging (DTI) realizes the observation of structural integrity and connectivity of brain regions of interest in vivo. However, it is unclear whether post-operative SF induces harmful changes in neurotransmitters and structures of the key brain regions and their contribution to POCD. In this study, we evaluated the effects of post-operative SF on neurotransmitter metabolism and structural integrity of medial septum and hippocampal CA1 in aged C57BL/6J male mice. The animals received a 24-h SF procedure after isoflurane anesthesia and right carotid artery exposure surgery. 1H-MRS results showed after post-operative SF, the glutamate (Glu)/creatine (Cr) and glutamate + glutamine (Glx)/Cr ratios increased in the medial septum and hippocampal CA1, while the NAA/Cr ratio decreased in the hippocampal CA1. DTI results showed post-operative SF decreased the fractional anisotropy (FA) of white matter fibers in the hippocampal CA1, while the medial septum was not affected. Moreover, post-operative SF aggravated subsequent Y-maze and novel object recognition performances accompanied by abnormal enhancement of glutamatergic metabolism signal. This study suggests that 24-h SF induces hyperglutamate metabolism level and microstructural connectivity damage in sleep and cognitive brain regions in aged mice, which may be involved in the pathophysiological process of POCD

Reprogrammed tracrRNAs enable repurposing of RNAs as crRNAs and sequence-specific RNA biosensors

In type II CRISPR systems, the guide RNA (gRNA) comprises a CRISPR RNA (crRNA) and a hybridized trans-acting CRISPR RNA (tracrRNA), both being essential in guided DNA targeting functions. Although tracrRNAs are diverse in sequence and structure across type II CRISPR systems, the programmability of crRNA-tracrRNA hybridization for Cas9 is not fully understood. Here, we reveal the programmability of crRNA-tracrRNA hybridization for Streptococcus pyogenes Cas9, and in doing so, redefine the capabilities of Cas9 proteins and the sources of crRNAs, providing new biosensing applications for type II CRISPR systems. By reprogramming the crRNA-tracrRNA hybridized sequence, we show that engineered crRNA-tracrRNA interactions can not only enable the design of orthogonal cellular computing devices but also facilitate the hijacking of endogenous small RNAs/mRNAs as crRNAs. We subsequently describe how these re-engineered gRNA pairings can be implemented as RNA sensors, capable of monitoring the transcriptional activity of various environment-responsive genomic genes, or detecting SARS-CoV-2 RNA in vitro, as an Atypical gRNA-activated Transcription Halting Alarm (AGATHA) biosensor