The Approaches from National Literature to World Literature

The paper explores the approaches from national literature to world one. The first approach to the world literature is literary translation and translated literature, the former refers to the faithful translation of original national works, and the latter means a creative treason of translation, or a kind of rewriting, based on the original text; the second is to gain the Nobel Award for Literature; The third is travel, exile or Diaspora of literature; and the last one is literary communication. In the end, the author stresses that the world literature is a literary garden of diversional and different dimension

Analysis of Stiffened Penstock External Pressure Stability Based on Immune Algorithm and Neural Network

The critical external pressure stability calculation of stiffened penstock in the hydroelectric power station is very important work for penstock design. At present, different assumptions and boundary simplification are adopted by different calculation methods which sometimes cause huge differences too. In this paper, we present an immune based artificial neural network model via the model and stability theory of elastic ring, we study effects of some factors (such as pipe diameter, pipe wall thickness, sectional size of stiffening ring, and spacing between stiffening rings) on penstock critical external pressure during huge thin-wall procedure of penstock. The results reveal that the variation of diameter and wall thickness can lead to sharp variation of penstock external pressure bearing capacity and then give the change interval of it. This paper presents an optimizing design method to optimize sectional size and spacing of stiffening rings and to determine penstock bearing capacity coordinate with the bearing capacity of stiffening rings and penstock external pressure stability coordinate with its strength safety. As a practical example, the simulation results illustrate that the method presented in this paper is available and can efficiently overcome inherent defects of BP neural network

Combined Anterior Sclera Staphylectomy and Vitrectomy with Anterior Sclera Staphyloma and Vitreous Hemorrhage Occurring 38 Years after Cataract Surgery

Introduction. To report a case of anterior sclera staphyloma and vitreous hemorrhage occurring over 38 years after bilateral cataract surgery. Methods. A 58-year-old man presented with anterior sclera staphyloma and vitreous hemorrhage in the right eye, after bilateral cataract surgery, over 38 years ago. We performed combined anterior sclera staphylectomy and vitrectomy of right eye for anterior sclera staphyloma and vitreous hemorrhage. Results. Forty-eight months after the combined surgery, best-corrected visual acuity was 0.3 (+10.00/−4.50 × 60) with eutopic stitches of the corneoscleral junction on the superior nasal quadrant and a stable ocular surface. Conclusions. This is the first reported case of anterior sclera staphyloma with vitreous hemorrhage successfully managed by combined surgery

A new high accuracy locally one-dimensional scheme for the wave equation

AbstractIn this paper, a new locally one-dimensional (LOD) scheme with error of O(Δt4+h4) for the two-dimensional wave equation is presented. The new scheme is four layer in time and three layer in space. One main advantage of the new method is that only tridiagonal systems of linear algebraic equations have to be solved at each time step. The stability and dispersion analysis of the new scheme are given. The computations of the initial and boundary conditions for the two intermediate time layers are explicitly constructed, which makes the scheme suitable for performing practical simulation in wave propagation modeling. Furthermore, a comparison of our new scheme and the traditional finite difference scheme is given, which shows the superiority of our new method

Floroindole confers protection against cecal ligation and puncture-induced sepsis via inhibition of NF-kB p65 phosphorylation

Purpose: To investigate the protective effect of floroindole against cecal ligation and puncture (CLP)- induced sepsis, as well as the underlying mechanism of action. Methods: Thirty-five 10–week-old male Wistar rats weighing 190 - 210 g (mean: 200.00 ± 10.10 g) were used for this study. The rats were randomly assigned to seven groups of five rats each, viz, normal control group, and six CLP groups. The CLP groups were those subjected to cecal ligation and puncture (CLP). The first 5 CLP groups received 2, 4, 6, 8 or 10 mg/kg floroindole, respectively, 1 h after CLP, via intraperitoneal route (i.p.) while the 6th CLP group served as untreated control. Western blotting, enzyme-linked immunosorbent assay (ELISA) and real-time quantitative polymerase chain reaction (qRT-PCR) were used for the assessment of the expression levels of tumor necrosis factor-α (TNF- α), interleukn-6 (IL-6), nucleotide-binding oligomerization domain 2 (NOD2) and p-NF-κB p65. Results: Cecal ligation and puncture (CLP) significantly and time-dependently upregulated the expressions of TNF-α, IL-6 and NOD2 in intestinal tissues of rats (p < 0.05). However, treatment with floroindole significantly, and dose-dependently down-regulated CLP-induced expressions of these proteins (p < 0.05). Treatment of rats with floroindole also significantly and dose-dependently inhibited CLP-induced phosphorylation of NF-κB p65 in rat ileum (p < 0.05). Conclusion: The results obtained in this study demonstrate that floroindole confers some degree of protection against CLP-induced sepsis via inhibition of NF-κB p65 phosphorylation

Notoginsenoside R1 increases neuronal excitability and ameliorates synaptic and memory dysfunction following amyloid elevation

Neurodegeneration and synaptic dysfunction observed in Alzheimer's disease (AD) have been associated with progressive decrease in neuronal activity. Here, we investigated the effects of Notoginsenoside R1 (NTR1), a major saponin isolated from Panax notoginseng, on neuronal excitability and assessed the beneficial effects of NTR1 on synaptic and memory deficits under the Aβ-enriched conditions in vivo and in vitro. We assessed the effects of NTR1 on neuronal excitability, membrane ion channel activity, and synaptic plasticity in acute hippocampal slices by combining electrophysiological extracellular and intracellular recording techniques. We found that NTR1 increased the membrane excitability of CA1 pyramidal neurons in hippocampal slices by lowering the spike threshold possibly through a mechanism involving in the inhibition of voltage-gated K+ currents. In addition, NTR1 reversed Aβ1-42 oligomers-induced impairments in long term potentiation (LTP). Reducing spontaneous firing activity with 10 nM tetrodotoxin (TTX) abolished the protective effect of NTR1 against Aβ-induced LTP impairment. Finally, oral administration of NTR1 improved the learning performance of the APP/PS1 mouse model of AD. Our work reveals a novel mechanism involving in modulation of cell strength, which contributes to the protective effects of NTR1 against Aβ neurotoxicity

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities

Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition

Self-supervised skeleton-based action recognition enjoys a rapid growth along with the development of contrastive learning. The existing methods rely on imposing invariance to augmentations of 3D skeleton within a single data stream, which merely leverages the easy positive pairs and limits the ability to explore the complicated movement patterns. In this paper, we advocate that the defect of single-stream contrast and the lack of necessary feature transformation are responsible for easy positives, and therefore propose a Cross-Stream Contrastive Learning framework for skeleton-based action Representation learning (CSCLR). Specifically, the proposed CSCLR not only utilizes intra-stream contrast pairs, but introduces inter-stream contrast pairs as hard samples to formulate a better representation learning. Besides, to further exploit the potential of positive pairs and increase the robustness of self-supervised representation learning, we propose a Positive Feature Transformation (PFT) strategy which adopts feature-level manipulation to increase the variance of positive pairs. To validate the effectiveness of our method, we conduct extensive experiments on three benchmark datasets NTU-RGB+D 60, NTU-RGB+D 120 and PKU-MMD. Experimental results show that our proposed CSCLR exceeds the state-of-the-art methods on a diverse range of evaluation protocols.Comment: 15 pages, 7 figure