STUDY OF APPLICATION OF THZ TIME DOMAIN SPECTROSCOPY IN FOOD SAFETY

Abstract: In this paper, a new spectroscopy technology named terahertz time-domain spectroscopy (THz-TDS) is introduced, which is used in food safety. We describe a coherent subpicosecond THz spectroscopy system based on nonresonant optical rectification for the generation of THz radiation. As an example, we measured absorption spectrum of water vapor by THz-TDS in frequency from 0.5 to 2.5 THz, The experiment demonstrated that the spectroscopy resolution of system was up to 0.0001THz, which can be measured vegetable pesticide residual, for it neither need sample pretreatment nor cause pollution

Bearing fault diagnosis and degradation analysis based on improved empirical mode decomposition and maximum correlated kurtosis deconvolution

Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detected, earlier maintenance actions can be implemented. On the other hand, remaining useful life (RUL) prediction provides important information when the maintenance should be conducted. However, good degradation features are the prerequisite for effective RUL prediction. Therefore, this paper mainly concerns earlier fault detection and degradation feature extraction for bearing. Maximum correlated kurtosis deconvolution (MCKD) can enhance PIS produced by bearing fault. Whereas, it only achieve good effect when bearing has severe fault. On the contrary, PIS produced by bearing weak fault is always masked by heavy noise and cannot be enhanced by MCKD. In order to resolve this problem, a revised empirical mode decomposition (EMD) algorithm is used to denoise bearing fault signal before MCKD processing. In revised EMD algorithm, a new recovering algorithm is used to resolve mode mixing problem existed in traditional EMD and it is superior to ensemble EMD. For degradation analysis, correlated kurtosis (CK) value is used as degradation indicator to reflect health condition of bearing. Except of theory analysis, simulated bearing fault data, injected bearing fault data, real bearing fault data and bearing degradation data are used to verify the proposed method. Simulated bearing fault data is used to explain the existed problems. Then, injected bearing fault data and real bearing fault data are used to demonstrate the effectiveness of proposed method for fault diagnosis. Finally, bearing degradation data is used to verify the degradation feature CK extracted based on proposed method. All these case studies show the effectiveness of proposed fault diagnosis and degradation tracking method

Vaccaria hypaphorine alleviates lipopolysaccharide-induced inflammation via inactivation of NFκB and ERK pathways in Raw 264.7 cells

10.1186/s12906-017-1635-1BMC Complementary and Alternative Medicine17112

Bearing fault diagnosis and degradation analysis based on improved empirical mode decomposition and maximum correlated kurtosis deconvolution

Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detected, earlier maintenance actions can be implemented. On the other hand, remaining useful life (RUL) prediction provides important information when the maintenance should be conducted. However, good degradation features are the prerequisite for effective RUL prediction. Therefore, this paper mainly concerns earlier fault detection and degradation feature extraction for bearing. Maximum correlated kurtosis deconvolution (MCKD) can enhance PIS produced by bearing fault. Whereas, it only achieve good effect when bearing has severe fault. On the contrary, PIS produced by bearing weak fault is always masked by heavy noise and cannot be enhanced by MCKD. In order to resolve this problem, a revised empirical mode decomposition (EMD) algorithm is used to denoise bearing fault signal before MCKD processing. In revised EMD algorithm, a new recovering algorithm is used to resolve mode mixing problem existed in traditional EMD and it is superior to ensemble EMD. For degradation analysis, correlated kurtosis (CK) value is used as degradation indicator to reflect health condition of bearing. Except of theory analysis, simulated bearing fault data, injected bearing fault data, real bearing fault data and bearing degradation data are used to verify the proposed method. Simulated bearing fault data is used to explain the existed problems. Then, injected bearing fault data and real bearing fault data are used to demonstrate the effectiveness of proposed method for fault diagnosis. Finally, bearing degradation data is used to verify the degradation feature CK extracted based on proposed method. All these case studies show the effectiveness of proposed fault diagnosis and degradation tracking method

Visual Quality Assessment after Network Transmission Incorporating NS2 and Evalvid

On the basis of Evalvid tool integrated in NS2 (Network Simulator version 2), the paper gets new set of tools, myEvalvid, to establish the simulation and evaluation platform for multimedia transmission. Then the paper investigates the effects of various influence factors when multimedia information is transmitted in the network and the relationships among these factors. Based on the analysis, the paper gets different evaluation models, respectively. In this paper, we study the impact on performance of several basic source and network parameters of video streams, namely, GOP (Group of Pictures) pattern, compression quantitative parameters, packet length, and packet error rate. Simulation results show that different parameters lead to different distortion levels which are calculated according to the reconstruction images at the receiver and the original images. The experimental results show that the video transmission and quality evaluation model we designed can evaluate multimedia transmission performance over complex environment very well

Efficacy and safety of triazavirin therapy for coronavirus disease 2019 : A pilot randomized controlled trial

Acknowledgements: We are deeply grateful to the front-line clinicians who participated in the study while directly fighting the epidemic. This study was supported by the Chinese Academy of Engineering Projects for COVID-19 (2020-KYGG-01-04) and Heilongjiang Province Urgent Project-6 for COVID-19. Data and safety monitoring board members of this trial included Kang Li, Yong Zhang, Songjiang Liu, and Yaohui Shi.Peer reviewedPublisher PD

Spatially Resolving Spin-split Edge States of Chiral Graphene Nanoribbons

A central question in the field of graphene-related research is how graphene behaves when it is patterned at the nanometer scale with different edge geometries. Perhaps the most fundamental shape relevant to this question is the graphene nanoribbon (GNR), a narrow strip of graphene that can have different chirality depending on the angle at which it is cut. Such GNRs have been predicted to exhibit a wide range of behaviour (depending on their chirality and width) that includes tunable energy gaps and the presence of unique one-dimensional (1D) edge states with unusual magnetic structure. Most GNRs explored experimentally up to now have been characterized via electrical conductivity, leaving the critical relationship between electronic structure and local atomic geometry unclear (especially at edges). Here we present a sub-nm-resolved scanning tunnelling microscopy (STM) and spectroscopy (STS) study of GNRs that allows us to examine how GNR electronic structure depends on the chirality of atomically well-defined GNR edges. The GNRs used here were chemically synthesized via carbon nanotube (CNT) unzipping methods that allow flexible variation of GNR width, length, chirality, and substrate. Our STS measurements reveal the presence of 1D GNR edge states whose spatial characteristics closely match theoretical expectations for GNR's of similar width and chirality. We observe width-dependent splitting in the GNR edge state energy bands, providing compelling evidence of their magnetic nature. These results confirm the novel electronic behaviour predicted for GNRs with atomically clean edges, and thus open the door to a whole new area of applications exploiting the unique magnetoelectronic properties of chiral GNRs