Essential Tools of Linear Algebra for Calculating Nuclear Spin Dynamics of Chemically Exchanging Systems

In this work, we describe essential tools of linear algebra necessary for calculating the effect of chemical exchange on spin dynamics and polarization transfer in various nuclear magnetic resonance (NMR) experiments. We show how to construct Hamiltonian, relaxation, and chemical exchange superoperators in the Liouville space, as well as demonstrate corresponding code in Python. Examples of applying the code are given for problems involving chemical exchange between NH3 and NH4+ at zero and high magnetic field and polarization transfer from parahydrogen relevant in SABRE (signal amplification by reversible exchange) at low magnetic field (0-20 mT). The presented methodology finds utility for describing the effect of chemical exchange on NMR spectra and can be extended further by taking into account non-linearities in the master equation

13^{13}C and 15^{15}N benchtop NMR detection of metabolites via relayed hyperpolarization

Parahydrogen-based nuclear spin hyperpolarization allows various magnetic-resonance applications, and it is particularly attractive because of its technical simplicity, low cost, and ability to quickly (in seconds) produce large volumes of hyperpolarized material. Although many parahydrogen-based techniques have emerged, some of them remain unexplored due to the lack of careful optimization studies. In this work, we investigate and optimize a novel parahydrogen-induced polarization (PHIP) technique that relies on proton exchange referred to below as PHIP-relay. An INEPT (insensitive nuclei enhanced by polarization transfer) sequence is employed to transfer polarization from hyperpolarized protons to heteronuclei ($^{15}$N and $^{13}$C) and nuclear signals are detected using benchtop NMR spectrometers (1 T and 1.4 T, respectively). We demonstrate the applicability of the PHIP-relay technique for hyperpolarization of a wide range of biochemicals by examining such key metabolites as urea, ammonium, glucose, amino acid glycine, and a drug precursor benzamide. By optimizing chemical and NMR parameters of the PHIP-relay, we achieve a 17,100-fold enhancement of $^{15}$N signal of [$^{13}$C, $^{15}$N$_{2}$]-urea compared to the thermal signal measured at 1 T. We also show that repeated measurements with shorter exposure to parahydrogen provide a higher effective signal-to-noise ratio compared to longer parahydrogen bubbling

Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning

We introduce a new type of query mechanism for collecting human feedback, called the perceptual adjustment query ( PAQ). Being both informative and cognitively lightweight, the PAQ adopts an inverted measurement scheme, and combines advantages from both cardinal and ordinal queries. We showcase the PAQ in the metric learning problem, where we collect PAQ measurements to learn an unknown Mahalanobis distance. This gives rise to a high-dimensional, low-rank matrix estimation problem to which standard matrix estimators cannot be applied. Consequently, we develop a two-stage estimator for metric learning from PAQs, and provide sample complexity guarantees for this estimator. We present numerical simulations demonstrating the performance of the estimator and its notable properties.Comment: 42 pages, 6 figure

Investigation of lattice capacity effect on Cu²+-doped SnO₂ solid solution catalysts to promote reaction performance toward NOx-SCR with NH₃

To understand the effect of the doping amount of Cu²+ on the structure and reactivity of SnO₂ in NOx-SCR with NH3, a series of Sn-Cu-O binary oxide catalysts with different Sn/Cu ratios have been prepared and thoroughly characterized. Using the XRD extrapolation method, the SnO2 lattice capacity for Cu²+ cations is determined at 0.10 g CuO per g of SnO2, equaling a Sn/Cu molar ratio of 84/1

Potential Game Based Distributed IoV Service Offloading With Graph Attention Networks in Mobile Edge Computing

Vehicular services aim to provide smart and timely services (e.g., collision warning) by taking the advantage of recent advances in artificial intelligence and employing task offloading techniques in mobile edge computing. In practice, the volume of vehicles in the Internet of Vehicles (IoV) often surges at a single location and renders the edge servers (ESs) severely overloaded, resulting in a very high delay in delivering the services. Therefore, it is of practical importance and urgency to coordinate the resources of ESs with bandwidth allocation for mitigating the occurrence of a spike traffic flow. For this challenge, existing work sought the periodicities of traffic flow by analyzing historical traffic data. However, the changes in traffic flow caused by sudden traffic conditions cannot be obtained from these periodicities. In this paper, we propose a distributed traffic flow forecasting and task offloading approach named TFFTO to optimize the execution time and power consumption in service processing. Specifically, graph attention networks (GATs) are leveraged to forecast future traffic flow in short-term and the traffic volume is utilized to estimate the number of services offloaded to the ESs in the subsequent period. With the estimate, the current load of the ESs is adjusted to ensure that the services can be handled in a timely manner. Potential game theory is adopted to determine the optimal service offloading strategy. Extensive experiments are conducted to evaluate our approach and the results validate our robust performance

Suppression of Tumor Energy Supply by Liposomal Nanoparticle-Mediated Inhibition of Aerobic Glycolysis

Aerobic glycolysis enables cancer cells to rapidly take up nutrients (e.g., nucleotides, amino acids, and lipids) and incorporate them into the biomass needed to produce a new cell. In contrast to existing chemotherapy/radiotherapy strategies, inhibiting aerobic glycolysis to limit the adenosine 5′-triphosphate (ATP) yield is a highly efficient approach for suppressing tumor cell proliferation. However, most, if not all, current inhibitors of aerobic glycolysis cause significant adverse effects because of their nonspecific delivery and distribution to nondiseased organs, low bioavailability, and a narrow therapeutic window. New strategies to enhance the biosafety and efficacy of these inhibitors are needed for moving them into clinical applications. To address this need, we developed a liposomal nanocarrier functionalized with a well-validated tumor-targeting peptide to specifically deliver the aerobic glycolysis inhibitor 3-bromopyruvate (3-BP) into the tumor tissue. The nanoparticles effectively targeted tumors after systemic administration into tumor-bearing mice and suppressed tumor growth by locally releasing 3-BP to inhibit the ATP production of the tumor cells. No overt side effects were observed in the major organs. This report demonstrates the potential utility of the nanoparticle-enabled delivery of an aerobic glycolysis inhibitor as an anticancer therapeutic agent

Providing HIV-related services in China for men who have sex with men.

PROBLEM: In China, human immunodeficiency virus (HIV) care provided by community-based organizations and the public sector are not well integrated. APPROACH: A community-based organization and experts from the Guangzhou Center for Disease Control and Prevention developed internet-based services for men who have sex with men, in Guangzhou, China. The internet services were linked to clinical services offering HIV testing and care. LOCAL SETTING: The expanding HIV epidemic among men who have sex with men is a public health problem in China. HIV control and prevention measures are implemented primarily through the public system. Only a limited number of community organizations are involved in providing HIV services. RELEVANT CHANGES: The programme integrated community and public sector HIV services including health education, online HIV risk assessment, on-site HIV counselling and testing, partner notification, psychosocial care and support, counting of CD4+ T-lymphocytes and treatment guidance. LESSONS LEARNT: The internet can facilitate HIV prevention among a subset of men who have sex with men by enhancing awareness, service uptake, retention in care and adherence to treatment. Collaboration between the public sector and the community group promoted acceptance by the target population. Task sharing by community groups can increase access of this high-risk group to available HIV-related services

Novel Magnetic-Sensing Modalities with Nitrogen-Vacancy Centers in Diamond

In modern-day quantum metrology, quantum sensors are widely employed to detect weak magnetic fields or nanoscale signals. Quantum devices, exploiting quantum coherence, are inevitably connected to physical constants and can achieve accuracy, repeatability, and precision approaching fundamental limits. As a result, these sensors have shown utility in a wide range of research domains spanning both science and technology. A rapidly emerging quantum sensing platform employs atomic-scale defects in crystals. In particular, magnetometry using nitrogen-vacancy (NV) color centers in diamond has garnered increasing interest. NV systems possess a combination of remarkable properties, optical addressability, long coherence times, and biocompatibility. Sensors based on NV centers excel in spatial resolution and magnetic sensitivity. These diamond-based sensors promise comparable combination of high spatial resolution and magnetic sensitivity without cryogenic operation. The above properties of NV magnetometers promise increasingly integrated quantum measurement technology, as a result, they have been extensively developed with various protocols and find use in numerous applications spanning materials characterization, nuclear magnetic resonance (NMR), condensed matter physics, paleomagnetism, neuroscience and living systems biology, and industrial vector magnetometry. In this chapter, NV centers are explored for magnetic sensing in a number of contexts. In general, we introduce novel regimes for magnetic-field probes with NV ensembles. Specifically, NV centers are developed for sensitive magnetometers for applications where microwaves (MWs) are prohibitively invasive and operations need to be carried out under zero ambient magnetic field. The primary goal of our discussion is to improve the utility of these NV center-based magnetometers

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve