Hydrolytic and Photochemical Degradation of Organophosphorus Pesticides

To keep pace with demands for increasing food supplies to satisfy the expanding world population, modern agriculture has utilized the latest scientific and technological knowledge available. Increases in crop production through the use of growth regulators, fertilizers , herbicides, and insecticides have been little short of phenomenal, and drugs, feed additives, and higher-quality grain and forage have dramatically increased livestock production. But, as is usually the case, this progress has been accompanied by problems, one of the more serious being contamination of our environment by chemicals. Only in recent years have the full effects of these pollutants on the ecological balance of nature begun to be understood in all the intricacies and implications

Conformation of the Transmembrane Domain of the Anthrax Toxin Receptor

Restauració dels vitrallsFoto final, plafó a6, cara interna, amb llum a través. Geomètric

Metamorphosis of plasma turbulence-shear flow dynamics through a transcritical bifurcation

The structural properties of an economical model for a confined plasma turbulence governor are investigated through bifurcation and stability analyses. A close relationship is demonstrated between the underlying bifurcation framework of the model and typical behavior associated with low- to high-confinement transitions such as shear flow stabilization of turbulence and oscillatory collective action. In particular, the analysis evinces two types of discontinuous transition that are qualitatively distinct. One involves classical hysteresis, governed by viscous dissipation. The other is intrinsically oscillatory and non-hysteretic, and thus provides a model for the so-called dithering transitions that are frequently observed. This metamorphosis, or transformation, of the system dynamics is an important late side-effect of symmetry-breaking, which manifests as an unusual non-symmetric transcritical bifurcation induced by a significant shear flow drive.Comment: 17 pages, revtex text, 9 figures comprised of 16 postscript files. Submitted to Phys. Rev.

Quasar accretion disk sizes from continuum reverberation mapping in the DES standard-star fields

Measurements of the physical properties of accretion disks in active galactic nuclei are important for better understanding the growth and evolution of supermassive black holes. We present the accretion disk sizes of 22 quasars from continuum reverberation mapping with data from the Dark Energy Survey (DES) standard star fields and the supernova C fields. We construct continuum lightcurves with the \textit{griz} photometry that span five seasons of DES observations. These data sample the time variability of the quasars with a cadence as short as one day, which corresponds to a rest frame cadence that is a factor of a few higher than most previous work. We derive time lags between bands with both JAVELIN and the interpolated cross-correlation function method, and fit for accretion disk sizes using the JAVELIN Thin Disk model. These new measurements include disks around black holes with masses as small as $\sim10^7$ $M_{\odot}$, which have equivalent sizes at 2500\AA \, as small as $\sim 0.1$ light days in the rest frame. We find that most objects have accretion disk sizes consistent with the prediction of the standard thin disk model when we take disk variability into account. We have also simulated the expected yield of accretion disk measurements under various observational scenarios for the Large Synoptic Survey Telescope Deep Drilling Fields. We find that the number of disk measurements would increase significantly if the default cadence is changed from three days to two days or one day.Comment: 33 pages, 24 figure

Automatic detection of Ionospheric Alfvén Resonances in magnetic spectrograms using U-net

Ionospheric Alfven Resonances (IARs) are weak discrete non-stationary Alfven waves along magnetic field lines, at periods of ~0.5-20 Hz, that occur during local night-time, particularly during low geomagnetic activity. They are detectable through time-frequency analysis (spectrograms) of measurements made by sensitive search coil magnetometers. The IARs are generated by the interaction of electromagnetic energy partially trapped in the Earth-ionosphere cavity with the main geomagnetic field and their behavior provides proxy information about atmospheric ion density between 100-1000 km altitude. Limited methods exist to automatically detect and analyse their properties and behavior as they are difficult to extract using standard image and signal processing techniques. We present a new method for the detection of IARs based on the fully convolutional neural network U-net. U-net was chosen as it is able to perform accurate image segmentation and it can be trained in a supervised fashion on a relatively small labeled dataset utilizing data augmentation. We show that the resulting predictive model generated by training the U-net is able to detect IAR signals while mislabelling considerably less noise than other data analysis methods. We achieved our best results by using a training set of 178 hand-digitized examples from high-quality spectrograms measured at the Eskdalemuir Geophysical Observatory (UK). We find that the network converges in ten iterations with a final intersection over union (IoU) metric of 0.9 and a training loss of below 0.2. We use the trained network to extract IARs from over 2300 images, covering six years of search coil magnetometer data measured at the Eskdalemuir Observatory. U-net can also automatically handle missing data or days without IARs, giving a null result as expected. This constitutes the first use of a neural network for pattern recognition of unstructured image data such as spectrograms containing IAR signals, though the method is applicable to other types of resonances or geophysical features in the time-frequency domain

The Astropy Problem

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed, written, and operated as a grassroots, self-organized, almost entirely volunteer effort while the software is used by the majority of the astronomical community. Despite this, the project has always been and remains to this day effectively unfunded. Further, contributors receive little or no formal recognition for creating and supporting what is now critical software. This paper explores the problem in detail, outlines possible solutions to correct this, and presents a few suggestions on how to address the sustainability of general purpose astronomical software

FMRP Mediates mGluR(5)-Dependent Translation of Amyloid Precursor Protein

Amyloid precursor protein (APP) facilitates synapse formation in the developing brain, while beta-amyloid (Aβ) accumulation, which is associated with Alzheimer disease, results in synaptic loss and impaired neurotransmission. Fragile X mental retardation protein (FMRP) is a cytoplasmic mRNA binding protein whose expression is lost in fragile X syndrome. Here we show that FMRP binds to the coding region of APP mRNA at a guanine-rich, G-quartet–like sequence. Stimulation of cortical synaptoneurosomes or primary neuronal cells with the metabotropic glutamate receptor agonist DHPG increased APP translation in wild-type but not fmr-1 knockout samples. APP mRNA coimmunoprecipitated with FMRP in resting synaptoneurosomes, but the interaction was lost shortly after DHPG treatment. Soluble Aβ(40) or Aβ(42) levels were significantly higher in multiple strains of fmr-1 knockout mice compared to wild-type controls. Our data indicate that postsynaptic FMRP binds to and regulates the translation of APP mRNA through metabotropic glutamate receptor activation and suggests a possible link between Alzheimer disease and fragile X syndrome