66 research outputs found

    Using Moored Arrays and Hyperspectral Aerial Imagery to Develop Nutrient Criteria for New Hampshire\u27s Estuaries

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    Increasing nitrogen concentrations and declining eelgrass beds in Great Bay, NH are clear indicators of impending problems for the state’s estuaries. A workgroup established in 2005 by the NH Department of Environmental Services and the NH Estuaries Project (NHEP) adopted eelgrass survival as the water quality target for nutrient criteria development for NH’s estuaries. In 2007, the NHEP received a grant from the U.S. Environmental Protection Agency to collect water quality information including that from moored sensors and hyper-spectral imagery data of the Great Bay Estuary. Data from the Great Bay Coastal Buoy, part of the regional Integrated Ocean Observing System (IOOS), were used to derive a multivariate model of water clarity with phytoplankton, Colored Dissolved Organic Matter (CDOM), and non-algal particles. Non-algal particles include both inorganic and organic matter. Most of the temporal variability in the diffuse attenuation coefficient of Photosynthetically Available Radiation (PAR) was associated with non-algal particles. However, on a mean daily basis non-algal particles and CDOM contributed a similar fraction (~30 %) to the attenuation of light. The contribution of phytoplankton was about a third of the other two optically important constituents. CDOM concentrations varied with salinity and magnitude of riverine inputs demonstrating its terrestrial origin. Non-algal particle concentration also varied with river flow but also wind driven resuspension. Twelve of the NHEP estuarine assessment zones were observed with the hyperspectral aerial imagery on August 29 and October 17. A concurrent in situ effort included buoy measurements, continuous along-track sampling, discrete water grab samples, and vertical profiles of light attenuation. PAR effective attenuation coefficients retrieved from deep water regions in the imagery agreed well with in-situ observations. Water clarity was lower and optically important constituent concentrations were higher in the tributaries. Eelgrass survival depth, estimated as the depth at which 22% of surface light was available, ranged from less than half a meter to over two meters. The best water clarity was found in the Great Bay (GB), Little Bay (LB), and Lower Piscataqua River (LPR) assessment zones. Absence of eelgrass from these zones would indicate controlling factors other than water clarity

    Restoration of Oyster (Crassostrea virginica) Habitat for Multiple Estuarine Species Benefits

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    Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types

    Macroalgae and eelgrass mapping in Great Bay Estuary using AISA hyperspectral imagery

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    Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types

    Suppression of back-to-back hadron pairs at forward rapidity in d+Au Collisions at sqrt(s_NN)=200 GeV

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    Back-to-back hadron pair yields in d+Au and p+p collisions at sqrt(s_NN)=200 GeV were measured with the PHENIX detector at the Relativistic Heavy Ion Collider. Rapidity separated hadron pairs were detected with the trigger hadron at pseudorapidity |eta|<0.35 and the associated hadron at forward rapidity (deuteron direction, 3.0<eta<3.8). Pairs were also detected with both hadrons measured at forward rapidity; in this case the yield of back-to-back hadron pairs in d+Au collisions with small impact parameters is observed to be suppressed by a factor of 10 relative to p+p collisions. The kinematics of these pairs is expected to probe partons in the Au nucleus with low fraction x of the nucleon momenta, where the gluon densities rise sharply. The observed suppression as a function of nuclear thickness, p_T, and eta points to cold nuclear matter effects arising at high parton densities.Comment: 381 authors, 6 pages, 4 figures. Published in Phys. Rev. Lett. (http://link.aps.org/doi/10.1103/PhysRevLett.107.172301). v3 has minor changes to match published version (http://www.phenix.bnl.gov/phenix/WWW/info/pp1/128/PhysRevLett.107.172301) Plain text data tables for points plotted in figures are publicly available at http://www.phenix.bnl.gov/phenix/WWW/info/data/ppg128_data.htm

    Long-Term Sphere Culture Cannot Maintain a High Ratio of Cancer Stem Cells: A Mathematical Model and Experiment

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    Acquiring abundant and high-purity cancer stem cells (CSCs) is an important prerequisite for CSC research. At present, researchers usually gain high-purity CSCs through flow cytometry sorting and expand them by short-term sphere culture. However, it is still uncertain whether we can amplify high-purity CSCs through long-term sphere culture. We have proposed a mathematical model using ordinary differential equations to derive the continuous variation of the CSC ratio in long-term sphere culture and estimated the model parameters based on a long-term sphere culture of MCF-7 stem cells. We found that the CSC ratio in long-term sphere culture presented as gradually decreased drift and might be stable at a lower level. Furthermore, we found that fitted model parameters could explain the main growth pattern of CSCs and differentiated cancer cells in long-term sphere culture

    Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

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    The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain

    Deep Eutectic Solvents (DESs) and their applications [forthcoming]

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    Deep Eutectic Solvents (DESs) and Their Application

    Physicochemical Characterization of Passive Films and Corrosion Layers by Differential Admittance and Photocurrent Spectroscopy

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    Two different electrochemical techniques, differential admittance and photocurrent spectroscopy, for the characterization of electronic and solid state properties of passive films and corrosion layers are described and critically evaluated. In order to get information on the electronic properties of passive film and corrosion layers as well as the necessary information to locate the characteristic energy levels of the passive film/electrolyte junction like: flat band potential (Ufb), conduction band edge (EC) or valence band edge (EV), a wide use of Mott-Schottky plots is usually reported in corrosion science and passivity studies. It has been shown, in several papers, that the use of simple M-S theory to get information on the electronic properties and energy levels location at the film/electrolyte interface can be seriously misleading and/or conflicting with the physical basis underlying the M-S theory. A critical appraisal of this approach to the study of very thin and thick anodic passive film grown on base-metals (Cr, Ni, Fe, SS etc..) or on valve metals (Ta, Nb, W etc..) is reported in this work, together with possible alternative approach to overcome some of the mentioned inconsistencies. At this aim the theory of amorphous semiconductor Schottky barrier, introduced several years ago in the study of passive film/electrolyte junction, is reviewed by taking into account some of the more recent results obtained by the present authors. Future developments of the theory appears necessary to get more exact quantitative information on the electronic properties of passive films, specially in the case of very thin film like those formed on base metals and their alloys. The second technique described in this chapter, devoted to the physico-chemical characterization of passive film and corrosion layers, is a more recent technique based on the analysis of the photo-electrochemical answer of passive film/electrolyte junction under illumination with photons having suitable energy. Such a technique usually referred to as Photocurrent Spectroscopy (PCS) has been developed on the basis of the large research effort carried out by several groups in the 1970’s and aimed to investigate the possible conversion of solar energy by means of electrochemical cells. In this work the fundamentals of semiconductor/electrolyte junctions under illumination will be highlighted both for crystalline and amorphous materials. The role of amorphous nature and film thickness on the photo-electrochemical answer of passive film/solution interface is reviewed as well the use of PCS for quantitative analysis of the film composition based on a semi-empirical correlation between optical band gap and difference of electronegativity of film constituents previously suggested by the present authors. In this frame the results of PCS studies on valve metal oxides and valve metal mixed oxides will be discussed in order to show the validity of the proposed method. The results of PCS studies aimed to get information on passive film composition and carried out by different authors on base metals (Fe, Cr, Ni) and their alloys, including stainless steel, will be also compared with compositional analysis carried out by well-established surface analysis techniques

    A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

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    Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G x E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
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