Enhancing Grassland Productivity through Disease Management of Grass and Forage Species

The total area of grassland in China is about 400 million hectares, accounting for 41.7% of the country’s land area, which plays important role in ecological construction and food security assurance of the national. However, diseases of grass and forage limited the development of the pastoral agriculture. There are more than1500 new diseases were reported in the past 16 years with more and more new diseases were discovered. The damage to grassland is becoming more severe with the known diseases prevalent areas expanding

Characterizing and Subsetting Big Data Workloads

Big data benchmark suites must include a diversity of data and workloads to be useful in fairly evaluating big data systems and architectures. However, using truly comprehensive benchmarks poses great challenges for the architecture community. First, we need to thoroughly understand the behaviors of a variety of workloads. Second, our usual simulation-based research methods become prohibitively expensive for big data. As big data is an emerging field, more and more software stacks are being proposed to facilitate the development of big data applications, which aggravates hese challenges. In this paper, we first use Principle Component Analysis (PCA) to identify the most important characteristics from 45 metrics to characterize big data workloads from BigDataBench, a comprehensive big data benchmark suite. Second, we apply a clustering technique to the principle components obtained from the PCA to investigate the similarity among big data workloads, and we verify the importance of including different software stacks for big data benchmarking. Third, we select seven representative big data workloads by removing redundant ones and release the BigDataBench simulation version, which is publicly available from http://prof.ict.ac.cn/BigDataBench/simulatorversion/.Comment: 11 pages, 6 figures, 2014 IEEE International Symposium on Workload Characterizatio

Response of irradiated and bystander cells to charged particles in two-dimensional and three-dimensional colon models

The radiation-induced bystander effect, wherein unirradiated cells near to or sharing medium with irradiated cells express biological responses, most often has been studied in two-dimensional monolayer cultures, although some studies with three-dimensional models and in vivo have also shown bystander signaling. We have shown previously that DNA damage, measured as foci of the DNA repair-related protein 53BP1, occurs in unirradiated bystander cells in a three-dimensional skin epithelium model irradiated with protons or iron ions (Lumpkins et al., submitted). In the current work, we extend the studies to a second epithelial model, colon, with studies in both two-dimensional monolayer and a three-dimensional tissue model using Caco2 human colon epithelial cancer cells and AG01522 human fibroblasts. For the monolayer studies, Caco2 cells in exponential growth were irradiated then co-cultured, sharing medium in an insert system, with unirradiated cells. Cells were irradiated with 250 kVp X-rays at Massachusetts General Hospital or with 1 GeV/amu protons, silicon ions or iron ions at the National Space Radiation Laboratory at Brookhaven National Laboratory. At varying times after irradiation, cell damage was assayed as micronuclei (MN) induction or formation of 53BP1 foci in both irradiated and bystander cells. For the three-dimensional studies, AG01522 fibroblasts were embedded in a collagen gel, then Caco2 cells were grown on the top of the gel. Each three-dimensional construct was cut in half prior to irradiation, with one half irradiated then immediately placed in contact with the other, bystander, half for co-culture. At selected times after irradiation, irradiated and bystander construct halves were fixed and sectioned, and 53BP1 foci were counted. In monolayer culture, irradiated Caco2 cells showed a dose-dependent increased fraction of cells with MN after exposure to X-rays, protons, iron ions or silicon ions. Bystander Caco2 cells sharing medium with the irradiated cells also showed an increased fraction of cells with MN, reaching similar levels of ∼16% cells with MN, about a threefold increase over controls, after 1 Gy of all types of radiation. The fraction of cells with 53BP1 foci depended on radiation type and time of assay after irradiation, with the induction of foci generally greatest 5 h after irradiation and increasing with radiation dose. In bystander Caco2 cells, the appearance of foci generally was delayed, with the maximal fraction of cells showing foci at 12 h. In three-dimensional culture, after X-ray or proton exposure, cells showed similar trends to those seen in two-dimensional growth, i.e. with both the Caco2 and the AG01522 cells, the fraction of irradiated cells having 53BP1 foci reached a maximum at 5 h, but with bystander cells, the maximum occurred at 12 h after irradiation. This delay in the appearance of foci in bystander cells compared with irradiated cells is similar to our findings in the three-dimensional skin model composed of keratinocytes and fibroblasts. In summary, our data now show in two different epithelial tissue models in both two-dimensional and three-dimensional models, radiation-stimulated intercellular signaling results in substantial levels of DNA damage in unirradiated cells. Because Caco2 cells are a carcinoma cell line, the studies are now being extended to a three-dimensional colon model using normal human colonic epithelial cells

Stochastic spin-orbit-torque device as the STDP synapse for spiking neural networks

Neuromorphic hardware as a non-Von Neumann architecture has better energy efficiency and parallelism than the conventional computer. Here, with numerical modeling spin-orbit torque (SOT) device using current-induced SOT and Joule heating effects, we acquire its magnetization switching probability as a function of the input current pulses and use it to mimic the spike-timing-dependent plasticity learning behavior like actual brain working. We further demonstrate that the artificial spiking neural network (SNN) built by this SOT device can perform unsupervised handwritten digit recognition with the accuracy of 80% and logic operation learning. Our work provides a new clue to achieving SNN-based neuromorphic hardware using high-energy efficiency and nonvolatile spintronics nanodevicesComment: 8 pages, 5 figure