Shear banding in monodisperse polymer melt

We performed a series of molecular dynamics simulations on monodisperse polymer melts to investigate the formation of shear banding. Under high shear rates, shear banding occurs, which is accompanied with the entanglement heterogeneity intimately. Interestingly, the same linear relationship between the end-to-end distance $R_{ee}$ and entanglement density $Z$ is observed at homogeneous flow before the onset of shear banding and at shear banding state, where $R_{ee} \sim [ln(W_i^{0.87})- \xi_0]Z$ is proposed as the criterion to describe the dynamic force balance of molecular chain in flow with a high rate. We establish a scaling relation between the disentanglement rate $V_d$ and Weissenberg number $W_i$ as $V_d \sim W_i^{0.87}$ for stable flow in homogeneous shear and shear banding states. Deviating from this relation leads to force imbalance and results in the emergence of shear banding. The formation of shear banding prevents chain from further stretching and disentanglement. The transition from homogeneous shear to shear banding partially dissipates the increased free energy from shear and reduces the free energy of the system

Multiscale Latent-Guided Entropy Model for LiDAR Point Cloud Compression

The non-uniform distribution and extremely sparse nature of the LiDAR point cloud (LPC) bring significant challenges to its high-efficient compression. This paper proposes a novel end-to-end, fully-factorized deep framework that encodes the original LPC into an octree structure and hierarchically decomposes the octree entropy model in layers. The proposed framework utilizes a hierarchical latent variable as side information to encapsulate the sibling and ancestor dependence, which provides sufficient context information for the modelling of point cloud distribution while enabling the parallel encoding and decoding of octree nodes in the same layer. Besides, we propose a residual coding framework for the compression of the latent variable, which explores the spatial correlation of each layer by progressive downsampling, and model the corresponding residual with a fully-factorized entropy model. Furthermore, we propose soft addition and subtraction for residual coding to improve network flexibility. The comprehensive experiment results on the LiDAR benchmark SemanticKITTI and MPEG-specified dataset Ford demonstrates that our proposed framework achieves state-of-the-art performance among all the previous LPC frameworks. Besides, our end-to-end, fully-factorized framework is proved by experiment to be high-parallelized and time-efficient and saves more than 99.8% of decoding time compared to previous state-of-the-art methods on LPC compression

Effects of egg and vitamin A supplementation on hemoglobin, retinol status and physical growth levels of primary and middle school students in

Lack of protein and vitamin A influences the growth of student in impoverished mountain areas. The aim of the study was to assess the effects of egg and vitamin A supplementation on hemoglobin, serum retinol and anthropometric indices of 10-18 years old students of a low socioeconomic status. A total number of 288 students from four boarding schools were randomly selected by using cluster sampling method in Chongqing, and they were assigned into supplement group and control group non-randomly. Students in supplement group received a single 200,000 international units vitamin A and 1 egg/day (including weekends) for 6 months. The control group did not receive any supplementation. We measured hemoglobin, serum retinol and height and weight at baseline and after supplementation. The supplementation increased the mean hemoglobin concentration by 7.13 g/L compared with 1.38 g/L in control group (p<0.001), the mean serum retinol concentration by 0.31 μmol/L compared with 0.09 μmol/L in the control group (p=0.005), the mean height-for-age z score by 0.05 compared with 0.03 in the control group (p=0.319), the mean weight-for-age z score by 0.05 compared with -0.12 in the control group (p<0.001). Our results revealed that egg and vitamin A supplementation is an effective, convenient, and practical method to improve the levels of hemoglobin, serum retinol and prevent the deterioration of growth in terms of weight for primary and middle school students from outlying poverty-stricken areas. Our intervention did not have a beneficial effect on linear growth

CypB-CD147 Signaling Is Involved in Crosstalk between Cartilage and FLS in Collagen-Induced Arthritis

To investigate the crosstalk between cartilage and fibroblast-like synoviocytes (FLS) in rheumatoid arthritis (RA), we adopted an in vitro coculture system model of collagen-induced arthritis (CIA) cartilage and CIA FLS monolayer. CIA rat samples of the synovium and femur head were collected for isolation of FLS and coculture system. Cartilages were treated with vehicle (Ctrl group), 10 ng/mL interleukin- (IL-) 1α (IL-1α group), and 10 ng/mL IL-1α plus 10 μM dexamethasone (Dex group) for 3 days before coculture with FLS for further 2 days. After the coculture, FLS were collected to determine the influences of articular cartilage on synoviocytes. Whether the CypB-CD147 signaling pathway is involved in the interactions between cartilage and FLS is assayed. Results showed that IL-1α-stimulated CIA cartilage promoted the proliferation and reduced the apoptosis of FLS. Increased inflammatory cytokines and decreased p57 expression were found in cocultured FLS stimulated by IL-1α-challenged CIA cartilage. Upregulation of NF-κB and I-κB kinase β (IKK-β) and downregulation of the inhibitor of NF-κBα (I-κBα) protein were observed in cocultured FLS. After coculture, significant increases in the expression of cyclophilin B (CypB) and CD147 were observed in CIA cartilage and FLS, respectively. Furthermore, results of immunofluorescence staining showed that the anti-CD147 antibody significantly suppressed p65 nuclear translocation in cocultured FLS stimulated by IL-1α-challenged CIA cartilage. In conclusion, inflammatory effects in the cartilage-FLS coculture system are associated with the CypB-CD147 mediating NF-κB pathway which may further enhance the inflammation in RA

D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion Prediction

The non-uniformly distributed nature of the 3D dynamic point cloud (DPC) brings significant challenges to its high-efficient inter-frame compression. This paper proposes a novel 3D sparse convolution-based Deep Dynamic Point Cloud Compression (D-DPCC) network to compensate and compress the DPC geometry with 3D motion estimation and motion compensation in the feature space. In the proposed D-DPCC network, we design a {\it Multi-scale Motion Fusion} (MMF) module to accurately estimate the 3D optical flow between the feature representations of adjacent point cloud frames. Specifically, we utilize a 3D sparse convolution-based encoder to obtain the latent representation for motion estimation in the feature space and introduce the proposed MMF module for fused 3D motion embedding. Besides, for motion compensation, we propose a 3D {\it Adaptively Weighted Interpolation} (3DAWI) algorithm with a penalty coefficient to adaptively decrease the impact of distant neighbors. We compress the motion embedding and the residual with a lossy autoencoder-based network. To our knowledge, this paper is the first work proposing an end-to-end deep dynamic point cloud compression framework. The experimental result shows that the proposed D-DPCC framework achieves an average 76\% BD-Rate (Bjontegaard Delta Rate) gains against state-of-the-art Video-based Point Cloud Compression (V-PCC) v13 in inter mode

Study of the electronic structures of oxygen doped in LiBaF3 crystal

The most likely substituting positions of impurity oxygen ions in LiBaF3 crystals are studied using the general utility lattice program (GULP). The calculated results indicate that the main defect model is [OF′+VF·] in the O:LiBaF3 crystal. The electronic structures of the LiBaF3 crystal with the defect [OF′+VF·] are calculated using the DV-Xα method. It can be concluded from the electronic structures that the LiBaF3 crystal with the defect [OF′+VF·] will exhibit a 217–280 nm absorption band and the impurity oxygen will decrease core-valence luminescence yield

Ecological Risk Assessment and Source Apportionment of Heavy Metals in the Soil of an Opencast Mine in Xinjiang

To study the influence of open-pit coal mining on the surrounding soil environment and human health, this study selected the Hongshaquan coal mine in Xinjiang as the research area and took 31 soil samples from the dump and artificial forest of the mining area. The contents of seven heavy metals (As, Cd, Cr, Cu, Ni, Pb and Zn) in the soil were analyzed. The pollution index method, geoaccumulation index method (Igeo), potential ecological risk index method, health ecological risk assessment model and principal component analysis (PCA) were used to evaluate and analyze the heavy metal pollution, potential ecological risk and health ecological risk of the soil. The results showed that compared with the background value of soil in Xinjiang, except for Pb, other heavy metal elements were essentially pollution-free and belonged to the low ecological risk area. The health risk assessment model showed that Pb and As were the main pollution factors of noncarcinogenic risk, and that exposure to Ni, Pb and As had a lower carcinogenic risk. The PCA showed that Cu, Cr, Ni, Pb, As and Zn in the dump were from transportation and industrial activities, Cd was from natural resources, and Cr, Zn, Ni, Cd and Pb were from transportation in the artificial forest. Cu came from industrial sources and As from soil parent material. The dump was more seriously disturbed by human factors than by artificial forests. Our research provides a reference for heavy metal pollution and source analysis caused by mining

Application of Rice Husk Biochar and Earthworm on Concentration and Speciation of Heavy Metals in Industrial Sludge Treatment

The aim of this study was to assess the total concentration and speciation variation of heavy metals (Pb, Cd, Cu and Zn) during composting and vermicomposting of industrial sludge with different addition rations of rice husk biochar. Results indicated that pH, EC, total phosphorus (TP) and total potassium (TK) were increased and total organic carbon (TOC) and total nitrogen (TN) were decreased during the composting of industrial sludge with biochar compared with the control (sludge without biochar). The addition of earthworm to the biochar-amended sludge further decreased pH and TOC but highly enhanced the EC, TN, TP and TK. Comparatively lower concentrations of total and DTPA-extractable heavy metals were observed in biochar-amended sludge treatments mixed with earthworm in comparison with the biochar-amended sludge treatments without earthworm or the control. Sequential extraction methods demonstrated that vermicomposting of sludge with biochar converted more metals bound with exchangeable, carbonate and organic matter into the residual fraction in comparison with those composting treatments of sludge with biochar. As a result, the combination of rice husk biochar and earthworm accelerated the passivation of heavy metals in industrial sludge during vermicomposting. Rice husk biochar and earthworm can play a positive role in sequestering the metals during the treatment of industrial sludge. This research proposed a potential method to dispose the heavy metals in industrial sludge to transform waste into resource utilization