Application of wave based method for predicting the response of coupled vibro-acoustic system with unconstrained damping layer

The Wave Based Method (WBM) is a deterministic prediction method that is computational efficiency as compared to other deterministic prediction techniques in mid-frequency problems. This paper discusses the application of WBM for predicting the dynamic displacement of plate with an unconstrained damping layer based on Kirchhoff theory. Further, the prediction of acoustic response of the coupled vibro-acoustic system with unconstrained damping is realized on the use of WBM. A numerical example is introduced, and the comparison of numerical result obtained by WBM and FEM is acquired. It is seen that the WBM is applicable for vibro-acoustic system with unconstrained damping and is expected to yield faster and more accurate predictions. The limitation of the method caused by simplify hypothesis is described in combination with modelling ways and numerical results

Multiscale High-Level Feature Fusion for Histopathological Image Classification

Histopathological image classification is one of the most important steps for disease diagnosis. We proposed a method for multiclass histopathological image classification based on deep convolutional neural network referred to as coding network. It can gain better representation for the histopathological image than only using coding network. The main process is that training a deep convolutional neural network is to extract high-level feature and fuse two convolutional layers’ high-level feature as multiscale high-level feature. In order to gain better performance and high efficiency, we would employ sparse autoencoder (SAE) and principal components analysis (PCA) to reduce the dimensionality of multiscale high-level feature. We evaluate the proposed method on a real histopathological image dataset. Our results suggest that the proposed method is effective and outperforms the coding network

Medical Image Classification Based on Deep Features Extracted by Deep Model and Statistic Feature Fusion with Multilayer Perceptron‬

Medical image classification is a key technique of Computer-Aided Diagnosis (CAD) systems. Traditional methods rely mainly on the shape, color, and/or texture features as well as their combinations, most of which are problem-specific and have shown to be complementary in medical images, which leads to a system that lacks the ability to make representations of high-level problem domain concepts and that has poor model generalization ability. Recent deep learning methods provide an effective way to construct an end-to-end model that can compute final classification labels with the raw pixels of medical images. However, due to the high resolution of the medical images and the small dataset size, deep learning models suffer from high computational costs and limitations in the model layers and channels. To solve these problems, in this paper, we propose a deep learning model that integrates Coding Network with Multilayer Perceptron (CNMP), which combines high-level features that are extracted from a deep convolutional neural network and some selected traditional features. The construction of the proposed model includes the following steps. First, we train a deep convolutional neural network as a coding network in a supervised manner, and the result is that it can code the raw pixels of medical images into feature vectors that represent high-level concepts for classification. Second, we extract a set of selected traditional features based on background knowledge of medical images. Finally, we design an efficient model that is based on neural networks to fuse the different feature groups obtained in the first and second step. We evaluate the proposed approach on two benchmark medical image datasets: HIS2828 and ISIC2017. We achieve an overall classification accuracy of 90.1% and 90.2%, respectively, which are higher than the current successful methods

The anti-hepatic fibrosis effects of chlorogenic acid extracted from Artemisia Capillaris Herba on CCl4-induced mice via regulating TGF-β1/smad3 pathway

Introduction: Artemisia Capillaris Herba, a famous traditional Chinese medicine, is effective for the treatment of hepatic fibrosis(HF) in clinical applications. Research has confirmed that chlorogenic acid (CA), an organic acid compound was extracted from Artemisia Capillaris Herba, could reduce the hepatocyte injury induced by HF, however, its mechanism of anti-HF is still unclear, and we investigated whether CA could help treating HF mice. Methods: In this study, we evaluated the therapeutic effect of CA on HF mice induced by CCl4, which was extracted from Artemisia Capillaris Herba and identified by 1H NMR and 13C NMR spectroscopy. Seventy two NIH mice were divided into following groups: normal group, model group, low, medium and high dose of CA groups (7.5, 15, 30 mg/kg) and colchicine (Colc)-positive control group (0.2 mg/kg). All mice were injected 40% CCl4 for 8 weeks with a 24 h interval except normal mice. Each drug group and Colc group were given intragastric administration for 40 days while modeling. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), collage IV (Col-IV), hyaluronic acid (HA), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), procollagen typeⅢ (PC-Ⅲ), malondialdehyde (MDA) and laminin (LN) levels were detected by ELISA, samd3 and TGF-β1 were examined by immunohistochemistry and western blotting and the liver and kidney tissues were observed by HE. Results: At the end of administrations, the body weight of mice was decreased and the levels of ALT, AST, Col-IV, HA, IL-6, TNF-α, LN, PC-III, and MDA were increased in the HF modle mice compared with that of normal mice. Compared with the HF mice only, treatment with CA significantly decreased the levels of ALT, AST, Col-IV, HA, IL-6, TNF-α, LN, PC-III, and MDA. The HE staining results showed that the hepatic and nephritic injury were significantly alleviated after CA treatment. And the smad3 and TGF-β1 expression were inhibited in the CA-treated mice in comparison with the model mice. Conclusion: Conclusively, CA treatment could attenuate HF through the regulation of TGF-β1/smad3 pathway, suggesting that CA may be an effective component of Artemisia Capillaris Herba in the treatment of HF

Leaf Photosynthetic and Functional Traits of Grassland Dominant Species in Response to Nutrient Addition on the Chinese Loess Plateau

Leaf photosynthetic and functional traits of dominant species are important for understanding grassland community dynamics under imbalanced nitrogen (N) and phosphorus (P) inputs. Here, the effects of N (N0, N50, and N100, corresponding to 0, 50, and 100 kg ha−1 yr−1, respectively) or/and P additions (P0, P40, and P80, corresponding to 0, 40, and 80 kg ha–1 yr–1) on photosynthetic characteristics and leaf economic traits of three dominant species (two grasses: Bothriochloa ischaemum and Stipa bungeana; a leguminous subshrub: Lespedeza davurica) were investigated in a semiarid grassland community on the Loess Plateau of China. Results showed that, after a three-year N addition, all three species had higher specific leaf area (SLA), leaf chlorophyll content (SPAD value), maximum net photosynthetic rate (PNmax), and leaf instantaneous water use efficiency (WUE), while also having a lower leaf dry matter content (LDMC). The two grasses, B. ischaemum and S. bungeana, showed greater increases in PNmax and SLA than the subshrub L. davurica. P addition alone had no noticeable effect on the PNmax of the two grasses while it significantly increased the PNmax of L. davurica. There was an evident synergetic effect of the addition of N and P combined on photosynthetic traits and most leaf economic traits in the three species. All species had relatively high PNmax and SLA under the addition of N50 combined with P40. Overall, this study suggests that N and P addition shifted leaf economic traits towards a greater light harvesting ability and, thus, elevated photosynthesis in the three dominant species of a semiarid grassland community, and this was achieved by species–specific responses in leaf functional traits. These results may provide insights into grassland restoration and the assessment of community development in the context of atmospheric N deposition and intensive agricultural fertilization

Separation of Sr, Nd, and U from Geological Samples Using Tandem Resin Column

BACKGROUND Uranium-series nuclides are one of the three major radioactive decay systems, which are suitable for studying various geological processes at different time scales. In addition, 87Sr/86Sr and 143Nd/144Nd isotopes (Sr-Nd isotopes for short) are two commonly used isotopes, for rock dating, chemical weathering assessment and tracing sediment sources. In this case, the combination of Sr-Nd-U isotopes can provide more comprehensively knowledge of the element cycle on the earth's surface and deepen our understanding of the sediment "Source to Sink"processes.Most previous studies involving the Sr-Nd-U isotopes have been established by separating Sr-Nd and U isotopes respectively. In this way, the digestion operation must be performed twice, one for separating Sr-Nd and the other for separating U. Alternatively, if only one sample is digested for measuring all three isotopes, between each element separation, the residue must be dried and dissolved in another solution so as to start a new column work. The former increases the amount of samples, which is not conducive to analysis of precious and trace samples; the latter adds additional drying operation, which is time consuming and increases the risk of sample loss and contamination. OBJECTIVES To establish a new Sr-Nd-U combined separation scheme. In this method, only one sample is dissolved, avoiding solution transfer between each separation, so as to reduce sample amount and improve the efficiency of separation and purification of Sr-Nd-U isotopes. METHODS A new chromatographic scheme of separating Sr-Nd-U with one sample digestion using a tandem column scheme is presented. Three columns were overlain sequentially to separate Sr in Sr Spec column, Nd in AG50W-X8 column and U in UTEVA column. 3mol/L HNO3 was used to pre-condition, load the sample, and rinse the matrix. After rinsing the matrix, the tandem column was separated to 3 independent columns to elute the target elements (Sr, Nd, U) respectively.As the connection sequence of different resin columns may interfere with the recovery of target elements, two different chromatographic schemes were compared. In Scheme 1, U column was placed on top of Sr column, while in Scheme 2 the positions of U column and Sr resin column were exchanged. In both schemes, the AG50W-X8 resin column was set at the bottom as the cationic resin can adsorb the most complex elements.All separated elution was tested for element concentration using inductively coupled plasma-mass spectrometry (ICP-MS). The basalt standard sample (BCR-2) was used to examine the behavior and recovery of each element in the separation procedure. RESULTS A total of 10 fractions were recovered from the tandem column scheme, among which fraction 1 represented the leachate recovered by loading samples and rinsing matrix from the tandem three columns. Fraction 2, 5 and 8 represented the leachate recovered by Sr Spec resin, AG50W-X8 resin and UTEVA resin respectively rinsing matrix after separation of the three columns. Fraction 3, 6 and 9 represented the leachate recovered by Sr, REE and U columns, which was Sr, Nd and U collection. Fraction 4, 7 and 10 represented the leachate from each resin recycle stage.In either Scheme 1 or Scheme 2, most matrix elements (high content of K, Ca, Na, Mg, Al, Fe, Ti and P and low content of Rb, Hf and Th) were mainly concentrated in fraction 1. The elution rate of Na, Ti, Rb and Hf was up to 99%. The elution rate of K and Ca was slightly lower at about 85% and the elution rate of Fe was about 56%. Sr was mainly concentrated in fraction 3, which contained only a small amount of P and Ba. Nd was mainly concentrated in fraction 6, which also contained both Sm and Ce. U was mainly concentrated in fraction 9, which only contained a very small amount of P and Pb. The column recovery was almost 99.9% for U, 90% for Sr and over 80% for Nd.The removal rate of major matrix elements (K, Ca, Na, Ba, Fe, Rb, etc.) exceeded 99%, which reduced interference with high-precision isotope analysis of Sr, Nd, and U. The recovery and purity of Sr, Nd, U were all quite high. A very small amount of P and Ba in fraction 3 had no interference with Sr isotopes (87Sr/86Sr). The Rb which was isomorphism of Sr was removed completely. With regard to Sm and Ce in fraction 6, previous studies had shown that 142Ce could not interfere with Nd isotope (143Nd/144Nd), and Sm could be further separated by Ln resin, so as not to affect Nd isotopic test. Fraction 9 contained nearly 100% U with no other elements.The sequence of resin column splicing is a crucial consideration which may impact the element separation. Hence, the position of Sr Spec column and UTEVA column was exchanged to compare the influence of different column sequences on eluting target elements. Both Scheme 1 and Scheme 2 can effectively wash off most of the matrix elements, and the target elements Sr, Nd and U can be efficiently adsorbed on the resin. There is no significant difference on target element separation between the two different column sequences. This indicates that Sr Spec and UTEVA resins do not interfere with each other on the target elements. CONCLUSIONS The new chromatographic scheme of separating Sr-Nd-U with one sample digestion using a tandem column scheme can be used to quickly and efficiently separate Sr, Nd and U elements from silicate rock samples. The recovery rate for U, Sr and Nd is 99.9%, 92.5% and 82.1%, respectively, which meet the requirements of subsequent isotope analysis. This Sr-Nd-U combined separation method can be used to reduce the sample consumption by about 50%, which is beneficial to the analysis of precious and trace samples. Meanwhile, as no solution transfer is needed between each column separation, this method can also save time for column work and increase the efficiency of chemical separation. A new idea for Sr-Nd-U multi-isotope separation is provided. If the recovery of Pb in the fraction 4 of this chromatographic scheme can be improved in further studies, the application of this new method may be expanded to more fields in the future

Smithian and Spathian (Early Triassic) conodonts from Oman and Croatia and their depth habitat revealed

Conodont ecology of the Early Triassic Smithian–Spathian transition is still poorly understood. Here we use oxygen isotope ratios of monogeneric conodonts from Omani samples to reveal the differences of oxygen isotopic composition between different taxa. Oxygen isotope analyses from Oman reveal that Neogondolella inhabited a deeper part of the water column relative to neospathodids and Icriospathodus. This indicates that species of Neogondolella lived in an environment ca. 1.7 °C cooler than where neospathodids lived. The investigation of conodonts from these Smithian and Spathian sections has also enabled the first recovery of some rarely reported species (e.g., Icriospathodus zaksi, Paullella omanensis sp. nov. Chen and Gladigondolella laii sp. nov. Chen) from Oman. Paullella omanensis sp. nov. was further recovered from Plavno, Croatia, indicating a large geographic distribution, and its value for biostratigraphic correlations. The discovery of these species in both Oman and Croatia expands their geographical distribution