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

Catalpol protects mouse ATDC5 chondrocytes against interleukin-1β-induced catabolism

Catalpol is a natural product with promising anti-inflammatory effects, however, its effects on chondrocytes and osteoarthritis (OA) have not been well investigated. OA is a painful and debilitating joint disease that affects people worldwide. Traditional Chinese Medicine has been sought to treat OA, including the Rehmannia extract, Catalpol. Here, we examined the effects of Catalpol, a plant derivative used in traditional Chinese medicine, on ATDC5 chondrocytes originating from mouse teratocarcinoma cells stimulated with interleukin-1β (IL-1β) to mimic the OA cellular environment. Catalpol significantly reduced matrix metalloproteinase-1, -3, -13 (MMP-1, -3, -13), a disintegrin and metalloproteinase with thrombospondin motifs -4, -5 (ADAMTS-4, -5) against IL-1β, demonstrating a likely anti-cartilage degradation activity. We also found that Catalpol exerted a significant antioxidative stress effect by downregulating the production of inducible nitric oxide synthase (iNOS), nitric oxide (NO), reactive oxygen species (ROS), and malondialdehyde (MDA). Catalpol treatment significantly reduced the levels of several key inflammatory factors, including Prostaglandin E2 (PGE2), cyclooxygenase-2 (COX-2), interleukin-8 (IL8), and monocyte chemoattractant protein-1 (MCP-1). We further demonstrate that the effects of Catalpol were mediated by the nuclear factor -κB (NF-κB) pathway via downregulation of the phosphorylation of inhibitor of nuclear factor κB-α (IκBα). This was confirmed by measuring p38 and p65 protein levels as well as the luciferase activity of NF-κB. Altogether, we demonstrate the potential of Catalpol as a novel treatment agent against cartilage matrix degradation, oxidative stress, and inflammation in OA

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

Effect of light injection on the security of practical quantum key distribution

Quantum key distribution (QKD) based on the fundamental laws of quantum physics can allow the distribution of secure keys between distant users. However, the imperfections in realistic devices may lead to potential security risks, which must be accurately characterized and considered in practical security analysis. High-speed optical modulators, being as one of the core components of practical QKD systems, can be used to prepare the required quantum states. Here, we find that optical modulators based on LiNbO3, including phase modulators and intensity modulators, are vulnerable to photorefractive effect caused by external light injection. By changing the power of external light, eavesdroppers can control the intensities of the prepared states, posing a potential threat to the security of QKD. We have experimentally demonstrated the influence of light injection on LiNbO3-based optical modulators and analyzed the security risks caused by the potential green light injection attack, along with the corresponding countermeasures

Microplastics alter soil structure and microbial community composition

Microplastics (MPs), including conventional hard-to-biodegrade petroleum-based and faster biodegradable plant-based ones, impact soil structure and microbiota in turn affecting the biodiversity and functions of terrestrial ecosystems. Herein, we investigated the effects of conventional and biodegradable MPs on aggregate distribution and microbial community composition in microhabitats at the aggregate scale. Two MP types (polyethylene (PE) and polylactic acid (PLA) with increasing size (50, 150, and 300 μm)) were mixed with a silty loam soil (0–20 cm) at a ratio of 0.5 % (w/w) in a rice–wheat rotation system in a greenhouse under 25 °C for one year. The effects on aggregation, bacterial communities and their co-occurrence networks were investigated as a function of MP aggregate size. Conventional and biodegradable MPs generally had similar effects on soil aggregation and bacterial communities. They increased the proportion of microaggregates from 17 % to 32 %, while reducing the macroaggregates from 84 % to 68 %. The aggregate stability decreased from 1.4 mm to 1.0–1.1 mm independently of MP size due to the decline in the binding agents gluing soil particles (e.g., microbial byproducts and proteinaceous substances). MP type and amount strongly affected the bacterial community structure, accounting for 54 % of the variance. Due to less bioavailable organics, bacterial community composition within microaggregates was more sensitive to MPs addition compared to macroaggregates. Co-occurrence network analysis revealed that MPs exacerbated competition among bacteria and increased the complexity of bacterial networks. Such effects were stronger for PE than PLA MPs due to the higher persistence of PE in soils. Proteobacteria, Bacteroidetes, Chloroflexi, Actinobacteria, and Gemmatimonadetes were the keystone taxa in macroaggregates, while Actinobacteria and Chloroflexi were the keystone taxa in microaggregates. Proteobacteria, Actinobacteria, and Chloroflexi were the most sensitive bacteria to MPs addition. Overall, both conventional and biodegradable MPs reduced the portion of large and stable aggregates, altering bacterial community structures and keystone taxa, and consequently, the functions

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