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Waterlogging remains a critical constraint to wheat production in areas with high rainfall. Exogenous application of nitrogen (N) can effectively diminish the adverse effects of waterlogging, but varies with specific events. To provide highly efficient remedial strategies, this pot study investigated the effects of urea application following 10 days of waterlogging initialing at the stem elongation stage (Zadoks growth stage, GS33). The remedial measures included foliar spray of urea solution at a single dose (0.108 g urea per pot) at the 0th day after finishing waterlogging (FU1) and twice at the 0th and 7th day (FU2), and soil surface spray of urea solution at single and double doses when soil water content was approximately 80% of field capacity (SU1 and SU2, respectively). Waterlogging significantly reduced grain yield, total N uptake, and N partial factor productivity (by 11%, 18%, and 11%, respectively), but subsequent remedial measures improved these to variable degrees. Reduction in grain yield owing to waterlogging could be effectively alleviated and even eliminated using these remediations. Grain yield and N partial factor productivity were higher under FU2 and SU2 than FU1 and SU1. Among all treatments, plants under SU2 exhibited the highest total N uptake and top-dressing N recovery. Diminished yield losses were attributed to (1) increased kernel number per spike resulting from increased spikelet fertility and kernel number per spikelet and (2) increased photosynthetic production by delaying senescence (improved chlorophyll content and maintained green leaf area) of the top leaves. This study suggests that urea application for a brief period of time following waterlogging during the stem elongation stage has remarkable remedial effects.

One of the key concerns in geographic modeling is the preparation of input data that are sufficient and appropriate for models. This requires considerable time, effort, and expertise since geographic models and their application contexts are complex and diverse. Moreover, both data and data pre-processing tools are multi-source, heterogeneous, and sometimes unavailable for a specific application context. The traditional method of manually preparing input data cannot effectively support geographic modeling, especially for complex integrated models and non-expert users. Therefore, effective methods are urgently needed that are not only able to prepare appropriate input data for models but are also easy to use. In this review paper, we first analyze the factors that influence data preparation and discuss the three corresponding key tasks that should be accomplished when developing input data preparation methods for geographic models. Then, existing input data preparation methods for geographic models are discussed through classifying into three categories: manual, (semi-)automatic, and intelligent (i.e., not only (semi-)automatic but also adaptive to application context) methods. Supported by the adoption of knowledge representation and reasoning techniques, the state-of-the-art methods in this field point to intelligent input data preparation for geographic models, which includes knowledge-supported discovery and chaining of data pre-processing functionalities, knowledge-driven (semi-)automatic workflow building (or service composition in the context of geographic web services) of data preprocessing, and artificial intelligent planning-based service composition as well as their parameter-settings. Lastly, we discuss the challenges and future research directions from the following aspects: Sharing and reusing of model data and workflows, integration of data discovery and processing functionalities, task-oriented input data preparation methods, and construction of knowledge bases for geographic modeling, all assisting with the development of an easy-to-use geographic modeling environment with intelligent input data preparation.

The phospholipids (PLs) of large yellow croaker (Pseudosciaena crocea, P. crocea) roe contain a high level of polyunsaturated fatty acids, especially docosahexaenoic acid (DHA), which can lower blood lipid levels. In previous research, PLs of P. crocea roe were found able to regulate the accumulation of triglycerides. However, none of these involve the function of DHA-containing phosphatidylcholine (DHA-PC), which is the main component of PLs derived from P. crocea roe. The function by which DHA-PC from P. crocea roe exerts its effects has not yet been clarified. Herein, we used purified DHA-PC and oleic acid (OA) induced HepG2 cells to establish a high-fat model, and the cell activity and intracellular lipid levels were then measured. The mRNA and protein expression of Fatty Acid Synthase (FAS), Carnitine Palmitoyl Transferase 1A (CPT1A) and Peroxisome Proliferator-Activated Receptor α (PPARα) in HepG2 cells were detected via RT-qPCR and western blot as well. It was found that DHA-PC can significantly regulate triglyceride accumulation in HepG2 cells, the effect of which was related to the activation of PPARα receptor activity, upregulation of CPT1A, and downregulation of FAS expression. These results can improve the understanding of the biofunction of hyperlipidemia mediated by DHA-PC from P. crocea roe, as well as provide a theoretical basis for the utilization of DHA-PC from P. crocea roe as a functional food additive.

[Purpose/significance] Knowledge management is an important course in library science. In order to promote the combination of theory and practice, it is necessary to reshape the teaching mode of “knowledge management” course. [Method/process] This paper combed the status quo of “knowledge management” course teaching at home and abroad, and then introduced the course teaching of “knowledge management” based on knowledge management method from two aspects: teaching stage and teaching topic. [Result/conclusion] This paper summarizes the teaching effect of knowledge management method. This course embodies the spirit of “sharing, management and innovation”, and focuses on training students’ knowledge organization ability, planning and design ability and logicality, hoping to guide the further development of domestic “knowledge management” course.

Background: Mesenchymal stem cells are capable of self-renewal and multi-lineage differentiation. They are used extensively to treat several diseases. Traditionally, mesenchymal stem cells are cultured in serum-containing media, typically supplemented with fetal bovine serum (FBS). However, the variability of FBS is likely to skew experimental results. Although serum-free media used to expand mesenchymal stem cells has facilitated remarkable achievements, immunomodulation of these cells in under serum-free conditions is poorly understood. We hypothesized that mesenchymal stem cells expanded in serum-free media will retain powerful immunoregulatory functions in vitro and in vivo. Design and Methods: Immunosuppressive activity and the immunomodulatory cytokines produced by mesenchymal stem cells in serum-free media were characterized in vitro. Immunomodulation by serum-free mesenchymal stem cell expansion in monocrotaline-induced pulmonary hypertension was explored in vivo. Results: Similar to cells in serum-containing media, mesenchymal stem cells expanded in serum-free media inhibited proliferation and apoptosis of CD4+T cells. They also exhibited strong immunosuppressive activities and secreted high levels of immunomodulatory cytokines such as PGE2, IDO1, COX2, IL-6, and IL-1β, but not HGF. On the other hand, growth of mesenchymal stem cells in serum-free media attenuated pulmonary vascular remodeling and inhibited mRNA expression of proinflammatory cytokines TNF-α, IFN-γ, IL-6, IL-1β, and IL-18. Conclusions: Mesenchymal stem cells in serum-free media maintained powerful immunomodulatory function in vitro and in vivo; serum-free media may replace serum-containing media for basic research and clinical applications.

Two novel binuclear Mn(II) metal-organic coordination complexes [Mn2(TBZ)2(CDC)(C2O4)]n (1), {[Mn2(TBZ)2(BDC)0.5(BTC)(H2O)2]·ET}n (2), (where TBZ = thiabendazole, H2CDC = trans-1,4-cyclohexanedicarboxylic acid, H2C2O4 = oxalic acid, H3BTC = 1,3,5-benzenetricarboxylic acid, ET = ethanol, H2BDC = 1,4-benzenedicarboxylate) have been hydrothermally synthesized and characterized by elemental analysis, IR spectroscopy, thermogravimetric analysis, electrochemical analysis and single crystal X-ray diffraction. The X-ray structure analysis reveals that 1 is s two-dimensional layer and 2 is s one-dimensional chain. In complex 1, it reveals 2-D layers composed of multi-(bidentate) bridging ligands (CDC and C2O4), and in 2, the coordinated BTC ligands adopt a monodentate mode and with BDC ligands adopt alternately chelating Mn1 and Mn2 bridges into 1-D chains. The 3-D structures of the two complexes are stabilized by π-π stacking interactions and hydrogen bonds.

There is no appropriate internal isolation mechanism for important production information system based on cloud computing. Here the main access control technologies were compared thoroughly and then two-layer key manage-ment scheme was put forward. In terms of the first layer, access control polynomial based on one-way hash function was constructed to achieve the separation of information flow between subgroups, that is, the information isolation within any department of a company was accomplished. Based on the first layer, a hierarchical key management was presented for different subgroups so as to realize the access control between different departments of a company. Then the security and complexity were analyzed. Finally, through the example and simulation experiment, the access control model based on two-layer key management scheme was verified.

A novel real-time digital nonlinearity post-calibration method was developed based on the Volterra series.With the purpose of fitting the inverse transfer function of the nonlinear distortion characteristics of the receiver,parameters of the model were measured and self-adaptively updated without knowledge of the inputs using the blind identification cri-terion that was aimed at the minimizing of the total energy of the frequencies other than strong signals in the calibrated outputs.Experimental results on multi-tone excitation and 16-QAM modulation input show that with the proposed method,spurs-free-dynamic-range（SFDR） of the high efficiency nonlinear receiver front-end would achieve almost 26dB improvement,and the ability of the system in weak signals detection can be also significantly enhanced.

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Adenylate kinase (AK) from Escherichia coli was used as both solubility and affinity tag for recombinant protein production. When fused to the N-terminus of a target protein, an AK fusion protein could be expressed in soluble form and purified to near homogeneity in a single step from Blue-Sepherose via affinity elution with micromolar concentration of P1, P5- di (adenosine-5') pentaphosphate (Ap5A), a transition-state substrate analog of AK. Unlike any other affinity tags, the level of a recombinant protein expression in soluble form and its yield of recovery during each purification step could be readily assessed by AK enzyme activity in near real time. Coupled to a His-Tag installed at the N-terminus and a thrombin cleavage site at the C terminus of AK, the streamlined method, here we dubbed AK-TAG, could also allow convenient expression and retrieval of a cleaved recombinant protein in high yield and purity via dual affinity purification steps. Thus AK-TAG is a new addition to the arsenal of existing affinity tags for recombinant protein expression and purification, and is particularly useful where soluble expression and high degree of purification are at stake.

Developing a three-dimensional laminar flow in the entrance region of rectangular microchannels has been investigated in this paper. When the hydrodynamic development length is the same magnitude as the microchannel length, entrance effects have to be taken into account, especially in relatively short ducts. Simultaneously, there are a variety of non-continuum or rarefaction effects, such as velocity slip and temperature jump. The available data in the literature appearing on this issue is quite limited, the available study is the semi-theoretical approximate model to predict pressure drop of developing slip flow in rectangular microchannels with different aspect ratios. In this paper, we apply the lattice Boltzmann equation method (LBE) to investigate the developing slip flow through a rectangular microchannel. The effects of the Reynolds number (1 < Re < 1000), channel aspect ratio (0 < ε < 1), and Knudsen number (0.001 < Kn < 0.1) on the dimensionless hydrodynamic entrance length, and the apparent friction factor, and Reynolds number product, are examined in detail. The numerical solution of LBM can recover excellent agreement with the available data in the literature, which proves its accuracy in capturing fundamental fluid characteristics in the slip-flow regime.

It has been 10 years since the invention of differential display (DD), a conceptually simple methodology that allows the detection and identification of differentially expressed genes. In the past decade, the number of publications describing successful applications of DD has outnumbered those using any other competing methodologies, including subtractive hybridization, representational difference analysis, serial analysis of gene expression, and DNA microarrays. This review will provide a glimpse of the current progress made in DD technological development, refinement, and automation. Excellent examples of DD applications in studying a variety of biological problems, in such diverse biological systems as bacteria, yeast, flies, plants, and higher mammals, are presented to provide a roadmap for those who would like to pursue a fruitful gene “fishing” expedition. Some of the fundamental differences between DD and DNA microarrays are also discussed.

Differential display (DD) is a widely used method for identifying differentially expressed genes. To improve further the efficiency and reproducibility of the method, this report systematically examines four critical parameters of standard DD-PCR. Specifically, the study determined the optimal annealing temperature, elongation time, dNTP concentration, and arbitrary primer concentration. By using a thermal cycler that was capable of displaying a temperature gradient across a PCR plate, it was possible to determine (in a single experiment) the effect of different annealing temperatures. The optimal annealing temperature for a 13-mer arbitrary primer fell within a broad range of 40°C–50°C. Elongation times over a range of 30–120 s worked best. The optimal concentration for dNTPs was within a very broad range of 2–50 μM, with higher amounts allowing for greater pipetting accuracy. The most favorable concentration for the arbitrary primer was also within a broad range of 0.1–2.0 μM. A primer concentration below this range greatly reduced the efficiency of the amplification process. In conclusion, the experimental findings delineated the best possible DD conditions for a more reliable assessment of differential gene expression.

Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP) neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1) remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.