Description: Virioplankton is a key component of marine biosphere in maintaining diversity of microorganisms and stabilizing ecosystems. They also greatly contribute to nutrient recycles by releasing organic matter after lysis of hosts. We constructed the global viral oceanography database (gVOD) by collecting 10,931 viral abundance (VA) data and 727 viral production (VP) data, along with host and other oceanographic parameters when available. We expect that the gVOD will be a fundamental and very useful database for laboratory, field and modeling studies in marine ecology and biogeochemistry.

Description: Far Upstream Element (FUSE) Binding Protein 1 (FBP1), first identified as a single-stranded DNA (ssDNA) binding protein that binds to the FUSE, could modulate c-myc mRNA levels and also has been shown to regulate tumor cell proliferation and replication of virus. Typically, FBP1 could active the translation of p27kip1 (p27) and participate in tumor growth. However, the expression and roles of FBP1 in peripheral system lesions and repair are still unknown. In our study, we found that FBP1 protein levels was relatively higher in the normal sciatic nerves, significantly decreased and reached a minimal level at day 3, and then returned to the normal level at 4 weeks. Spatially, we observed that FBP1 had a major colocation in Schwann cells and FBP1 was connectd with Ki-67 and Oct-6. In vitro, we detected the decreased level of FBP1 and p27 in the TNF-α-induced Schwann cells proliferation model, while increased expression in cAMP-induced Schwann cells differentiation system. Specially, FBP1-specific siRNA-tranfected SCs did not show fine and longer morphological change after cAMP treatment and had a decreased motility compared to normal. At 3 days after cAMP treatment and SC/neuron co-cultures, p27 was transported to cytoplasm to form CDK4/6-p27 to participate in SCs differentiation. In conclusion, we speculated that FBP1 and p27 were involved in SCs proliferation and the following differentation in the sciatic nerve after crush by transporting p27 from nucleus to cytoplasm. J. Cell. Biochem. © 2013 Wiley Periodicals, Inc.

Description: Marine diazotrophs convert dinitrogen (N-2) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version 1) was published. Here, we present an updated version of the database (version 2), significantly increasing the number of in situ diazotrophic measurements from 13 565 to 55 286. Data points for N-2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184 %, 86 %, and 809 %, respectively. Version 2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N2 fixation rates. The measurements of N-2 fixation rates approximately follow a log-normal distribution in both version 1 and version 2. However, version 2 considerably extends both the left and right tails of the distribution. Consequently, when estimating global oceanic N-2 fixation rates using the geometric means of different ocean basins, version 1 and version 2 yield similar rates (43-57 versus 45-63 TgNyr (-1); ranges based on one geometric standard error). In contrast, when using arithmetic means, version 2 suggests a significantly higher rate of 223 +/- 30 TgNyr (-1) (mean +/- standard error; same hereafter) compared to version 1 (74 +/- 7 TgNyr (-1)). Specifically, substantial rate increases are estimated for the South Pacific Ocean (88 +/- 23 versus 20 +/- 2 TgNyr 1), primarily driven by measurements in the southwestern subtropics, and for the North Atlantic Ocean (40 +/- 9 versus 10 +/- 2 TgNyr (-1)). Moreover, version 2 estimates the N-2 fixation rate in the Indian Ocean to be 35 +/- 14 TgNyr (-1), which could not be estimated using version 1 due to limited data availability. Furthermore, a comparison of N-2 fixation rates obtained through different measurement methods at the same months, locations, and depths reveals that the conventional N-15(2) bubble method yields lower rates in 69% cases compared to the new N-15(2) dissolution method. This updated version of the database can facilitate future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687; Shao et al., 2022).

Description: An infrared detector is proposed that is based on a ferroelectric tunnel junction (FTJ) working under bolometer-like principles. Electron tunneling, either direct or indirect, through the ferroelectric barrier depends on the temperature of the devices. During tunneling, infrared radiation alters the polarization of the ferroelectric film via pyroelectricity, resulting in a change in the barrier height of the tunnel junction. A high temperature coefficient of resistance of up to −3.86% was observed at room temperature. These results show that the FTJ structure has potential to be adapted for use in uncooled infrared detectors.

Description: Chemical Research in Toxicology DOI: 10.1021/acs.chemrestox.7b00290

Description: Water, Vol. 10, Pages 806: Water Quality Prediction Model of a Water Diversion Project Based on the Improved Artificial Bee Colony–Backpropagation Neural Network Water doi: 10.3390/w10060806 Authors: Siyu Chen Guohua Fang Xianfeng Huang Yuhong Zhang Prediction of water quality which can ensure the water supply and prevent water pollution is essential for a successful water transfer project. In recent years, with the development of artificial intelligence, the backpropagation (BP) neural network has been increasingly applied for the prediction and forecasting field. However, the BP neural network frame cannot satisfy the demand of higher accuracy. In this study, we extracted monitoring data from the water transfer channel of both the water resource and the intake area as training samples and selected some distinct indices as input factors to establish a BP neural network whose connection weight values between network layers and the threshold of each layer had already been optimized by an improved artificial bee colony (IABC) algorithm. Compared with the traditional BP and ABC-BP neural network model, it was shown that the IABC-BP neural network has a greater ability for forecasting and could achieve much better accuracy, nearly 25% more precise than the BP neural network. The new model is particularly practical for the water quality prediction of a water diversion project and could be readily applied in this field.

Description: Sustainability, Vol. 10, Pages 2187: Synergy Degree Evaluation Based on Synergetics for Sustainable Logistics Enterprises Sustainability doi: 10.3390/su10072187 Authors: Juan Huang Yuhong Shuai Qi Liu Hang Zhou Zhenggang He Today, logistics activities have become a major source of pollution that affects the environment and green logistics is becoming a hot topic. A logistics company’s operating strategy determines the direction of logistics activities and impact degree of logistics activities on the environment. And in logistics enterprises, there is a direct relationship between efficiency and collaboration as collaboration can reduce logistics costs and the negative impact of the bullwhip effect and increase the service level. Synergy degree evaluation, therefore, is crucial to analyze collaboration, identify vulnerabilities, promote development and is also a key step in building a green logistics system. This paper employs Synergetics to comprehensively evaluate the synergy degree in sustainable logistics enterprises. First, Synergetics is introduced to evaluate the synergy degree of sustainable logistics enterprises and the basic Synergetics principles are presented. Second, based on the Law of the Factors of Production, the synergy elements and logistics enterprise content is divided into three main factors: subject elements, object elements and facility and equipment elements. Then, a measurement model and framework for the synergy degree of logistics enterprises is built. Finally, a case study is given to verify the effectiveness of the proposed model and framework. It was found that the higher the logistics enterprise synergy degree, the higher the efficiency.