课程文献中心 更多>>

关键词： Vetiver   Essential oil   Similarity   Differential spectroscopy   Differential chromatography  

摘要： Adulteration of essential oils is a common and serious problem. Adequate and fast methods are required to establish the authenticity and purity. GC-MS, H-1 and C-13 NMR were compared in combination with similarity calculations as well as differential spectroscopy and chromatography for the authentication and determination of purity of vetiver essential oils. In the investigation of eight commercial oils H-1 and C-13 NMR adequately detected all six adulterants encountered in four of the commercial samples, while GC-MS was not able to detect adulteration with vegetable oils. A great advantage of the combined use of similarity calculation and NMR is that the authenticity can be verified without the need of concomitant measurement of a standard sample. The calculation can be carried out with a registered reference spectrum, in the case of 1H NMR acquired using the same magnetic field, but in the case of C-13 NMR the spectrum can be obtained with another magnetic field. H-1 NMR has the advantage of high speed, and the results can be obtained within minutes. C-13 NMR was found to be superior in its ability to provide unequivocal identification of eventual adulterants, with differential spectroscopy revealing all signals of the adulterants.

关键词： Array waveguide devices   Crosstalk   Dielectric waveguides   Effective refractive index   Electron beam lithography   Phased arrays  

摘要： Y Here we demonstrate an ultra-compact 8-channel sinusoidal silicon waveguide array for an optical phased array. In our device, based on sinusoidal bending, the cross talk (CT) between waveguides can be efficiently reduced with a waveguide pitch of only 695 nm. For the transverse electric (TE) mode, the simulation results show that the insertion loss (IL) of the 100-mu m-long device is 0.1 dB and the CT between all waveguides is lower than -25 dB at 1550 nm. In the measurements, an IL of less than 1 dB and CT lower than -18 dB are obtained. Since the pitch is related to the beam-steering range and power consumption of the optical phased array, such an ultra-compact device could potentially be a good candidate to build the emitter for an energy-efficient optical phased array with a large field of view. (C) 2022 Optical Society of America

关键词： Univariate calibration   Boron-doped diamond   electrode   Differential pulse   voltammetry   Water analysis   Dilution analysis  

摘要： The contamination of water sources by anthropogenic activities is a topic of growing interest in the scientific community. Therefore, robust analytical techniques for the determination and quantification of multiple substances are needed, which often require complex and time-consuming procedures. In this context, we describe a univariate calibration method to determine emerging multi-class contaminants in different water sources. The instrumental setup is composed of a lab-made glass electrochemical cell with three electrodes: Pt counter, Ag/ AgCl reference, and BDD working electrodes. With this system, we were able to simultaneously quantify tertbutylhydroquinone, acetaminophen, estrone, sulfamethoxazole, enrofloxacin, caffeine, and ibuprofen by differential pulse voltammetry. Only two calibration solutions are required for the Single-shot Dilution Differential Pulse Voltammetric Calibration (SSD-DP-VC) method described here, which can significantly improve sample throughput. Two robust univariate calibration strategies were also applied and compared with SSD-DP-VC. The new method is simple, fast, and comparable with traditional calibration methods, showing similar precision and accuracy for all determinations evaluated.

关键词： Partial differential equations  

摘要： Neural networks are increasingly used widely in the solution of partial differential equations (PDEs). This letter proposes 3D-PDE-Net to solve the three-dimensional PDE. We give a mathematical derivation of a three-dimensional convolution kernel that can approximate any order differential operator within the range of expressing ability and then conduct 3D-PDE-Net based on this theory. An optimum network is obtained by minimizing the normalized mean square error (NMSE) of training data, and L-BFGS is the optimized algorithm of second-order precision. Numerical experimental results show that 3D-PDE-Net can achieve the solution with good accuracy using few training samples, and it is of highly significant in solving linear and nonlinear unsteady PDEs.

关键词： DNA methylation   cfDNA   Hepatocellular carcinoma   Early detection of cancer   Liver cirrhosis  

摘要： Background: Aberrant DNA methylation may offer opportunities in revolutionizing cancer screening and diagnosis. We sought to identify a non-invasive DNA methylation-based screening approach using cell-free DNA (cfDNA) for early detection of hepatocellular carcinoma (HCC). Methods: Differentially, DNA methylation blocks were determined by comparing methylation profiles of biopsyproven HCC, liver cirrhosis, and normal tissue samples with high throughput DNA bisulfite sequencing. A multi-layer HCC screening model was subsequently constructed based on tissue-derived differentially methylated blocks (DMBs). This model was tested in a cohort consisting of 120 HCC, 92 liver cirrhotic, and 290 healthy plasma samples including 65 hepatitis B surface antigen-seropositive (HBsAg+) samples, independently validated in a cohort consisting of 67 HCC, 111 liver cirrhotic, and 242 healthy plasma samples including 56 HBsAg+ samples. Results: Based on methylation profiling of tissue samples, 2321 DMBs were identified, which were subsequently used to construct a cfDNA-based HCC screening model, achieved a sensitivity of 86% and specificity of 98% in the training cohort and a sensitivity of 84% and specificity of 96% in the independent validation cohort. This model obtained a sensitivity of 76% in 37 early-stage HCC (Barcelona clinical liver cancer [BCLC] stage 0-A) patients. The screening model can effectively discriminate HCC patients from non-HCC controls, including liver cirrhotic patients, asymptomatic HBsAg+ and healthy individuals, achieving an AUC of 0.957(95% CI 0.939-0.975), whereas serum alpha-fetoprotein (AFP) only achieved an AUC of 0.803 (95% CI 0.758-0.847). Besides detecting patients with early-stage HCC from non-HCC controls, this model showed high capacity for distinguishing early-stage HCC from a high risk population (AUC=0.934;95% CI 0.905-0.963), also significantly outperforming AFP. Furthermore, our model also showed superior performance in distinguishing HCC with

关键词： host defense   nutrient deprivation   alveolar macrophages   lung   monocyte   type 2 immunity   helminth  

摘要： Macrophages are known to mediate anti-helminth responses, but it remains uncertain which subsets are involved or how macrophages actually kill helminths. Here, we show rapid monocyte recruitment to the lung after infection with the nematode parasite Nippostrongylus brasiliensis. In this inflamed tissue microenvironment, these monocytes differentiate into an alveolar macrophage (AM)-like phenotype, expressing both SiglecF and CD11c, surround invading parasitic larvae, and preferentially kill parasites in vitro. Monocyte-derived AMs (Mo-AMs) express type 2-associated markers and show a distinct remodeling of the chromatin landscape relative to tissue-derived AMs (TD-AMs). In particular, they express high amounts of arginase-1 (Arg1), which we demonstrate mediates helminth killing through L-arginine depletion. These studies indicate that recruited monocytes are selectively programmed in the pulmonary environment to express AM markers and an anti-helminth phenotype.

关键词： Differential privacy   Signed graph   Multi-agent systems   Privacy preserving algorithm  

摘要： This paper studies the differential privacy-preserving problem for multi-agent systems (MASs) in the presence of antagonistic information over signed digraph. As for the structurally balanced case, an epsilon-differential privacy algorithm is proposed, upon which some sufficient conditions guaranteeing almost sure bipartite consensus are given. Based on the above scheme, the tradeoff between the system performance and the privacy guarantee is elaborated, and the optimal noise is also devised. Moreover, the proposed privacy preserving scheme is further applied to the scenario of structurally unbalanced graph, where a criterion with respect to almost sure stability of the considered system is derived, as well as the privacy preserving condition. This extends the balanced interaction scenario, and consequently the cooperative multi-agent systems. Finally, numerical simulations are presented to demonstrate the effectiveness of our results. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Synthetic data   Generative adversarial network   Federated learning   Differential privacy  

摘要： Distributed machine learning has attracted much attention in the last decade with the widespread use of the Internet of Things. As a generative model, Generative Adversarial Network (GAN) has excellent empir-ical performance. However, the distributed storage of data and the fact that data cannot be shared for pri-vacy reasons in a federated learning setting bring new challenges to training GAN. To address this issue, we propose private FL-GAN, a differentially private GAN based on federated learning. By strategically combining the Lipschitz condition with differential privacy sensitivity, our model can generate high-quality synthetic data without sacrificing the training data's privacy. When communication between cli-ents becomes the main bottleneck for federated learning, we propose to use a serialized model-training paradigm, which significantly reduces communication costs. Considering the distributed data is often non-IID in reality, which poses challenges to modeling, we further propose universal private FL-GAN to approach this problem. We not only theoretically prove that our algorithms can provide strict privacy guarantees with differential privacy, but also experimentally demonstrate that our models can generate satisfactory data while protecting the privacy of the training data, even if the data is non-IID. (c) 2021 Elsevier B.V. All rights reserved.