Computerized Health Risk Appraisal Inventory.

4 p

Interpreting Your Health Risk Appraisal Printout.

2 p

Computerized Health Risk Appraisal Inventory.

4 p

Interpreting Your Health Risk Appraisal Printout.

2 p

Capabilities and limitations of a new thermal finite volume model for the evaluation of laser-induced thermo-mechanical retinal damage

Many experimental studies focus on the physical damage mechanisms of short-term exposure to laser radiation. In the nanosecond (ns) pulse range, damage in the Retinal Pigment Epithelium (RPE) will most likely occur at threshold levels due to bubble formation at the surface of the absorbing melanosome. The energy uptake of the melanosomes is one key aspect in modeling the bubble formation and damage thresholds. This work presents a thermal finite volume model for the investigation of rising temperatures and the temperature distribution of irradiated melanosomes. The model takes the different geometries and thermal properties of melanosomes into account, such as the heat capacity and thermal conductivity of the heterogeneous absorbing melanosomes and the surrounding tissue. This is the first time the size and shape variations on the melanosomes‘ thermal behavior are considered. The calculations illustrate the effect of the geometry on the maximum surface temperature of the irradiated melanosome and the impact on the bubble formation threshold. A comparison between the calculated bubble formation thresholds and the RPE cell damage thresholds within a pulse range of 3 to 5000 ns leads to a mean deviation of = 22 mJ ∕ cm2 with a standard deviation of = 21 mJ ∕ cm2. The best results are achieved between the simulation and RPE cell damage thresholds for pulse durations close to the thermal confinement time of individual melanosomes

Impact of oceanic floods on particulate metal inputs to coastal and deep-sea environments: A case study in the NW Mediterranean Sea

An exceptional flood event, accompanying a marine storm, was investigated simultaneously at the entrance and the exit of the Gulf of Lion's hydrosystem (NW Mediterranean) in December 2003. Cs, Cr, Co, Ni, Cu, Zn, Cd and Pb signatures of both riverine and shelf-exported particles indicate that continental inputs and resuspended prodeltaic sediments were intensively mixed with resuspended sediments from middle/outer shelf areas during advective transport. As a result, particles leaving the Gulf of Lion inherited the mean signature of shelf bottom sediments, exporting anthropogenic Pb and Zn out into the open sea. When assessing the particulate metal budget in relation with the event, it appears that the output fluxes accounted for between 15% and 60% of the input fluxes, depending on the element and the period of reference. This trend is also observed for annual budgets, which were drawn up by compiling the data from this study and the literature. Results evidenced that, except some element fluxes during extreme output scenario, outputs never counter-balance the inputs. In its current functioning, the Gulf of Lion's shelf seems to act as a retention/sink zone for particulate metals. Regarding anthropogenic fluxes, the contribution of the oceanic flood of December 2003 to the mean annual scenario is considerable. Environmental impacts onto coastal and deep-sea ecosystems should therefore tightly depend on both the intensity and the frequency of event-dominated sediment transport

Machine learning approach to improve drug discovery in natural product extracts

Current natural product (NP) research is limited by its reliance on bioassay-guided fractionation to identify bioactive compounds in mixtures. Computational approaches may improve NP research by correlating mass spectra (MS) and nuclear magnetic resonance spectra (NMR) of bioactive mixtures to their bioactivity patterns. In this study, I use artificial neural networks (ANNs) to correlate both MS and NMR data of 40 fractions of hops (Humulus lupulus) extract to inhibition of iNOS-mediated formation of nitric oxide (provided by the Stevens Lab at Oregon State University). Xanthohumol and its derivatives, constituents of hops extract, are known to exhibit this anti-inflammatory activity. An MS-based model, NMR-based model, a model that concatenates MS and NMR as a single input, and model that treats them as separate inputs were investigated. The MS-based model predicted bioactivity with lowest error (MSE = 0.685) and identified xanthohumol as the top anti-inflammatory compound. The NMR-based model, concatenated model, and multichannel model predicted bioactivity with higher error: MSE = 9.48, 8.05, and 7.58, respectively, but they identified several known bioactive molecules and associated proton shifts as top predictors. In conclusion, ANNs have been shown to usefully predict bioactivity from MS/NMR data.Keywords: Machine learning, artificial neural networks, mass spectra, nuclear magnetic resonance spectra, bioactivity, natural products, Humulus lupulus, xanthohumo

A passive GHz frequency-division multiplexer/demultiplexer based on anisotropic magnon transport in magnetic nanosheets

The emerging field of magnonics employs spin waves and their quanta, magnons, to implement wave-based computing on the micro- and nanoscale. Multi-frequency magnon networks allow for parallel data processing within single logic elements whereas this is not the case with conventional transistor-based electronic logic. However, a lack of experimentally proven solutions to efficiently combine and separate magnons of different frequencies has impeded the intensive use of this concept. In this Letter, we demonstrate the experimental realization of a spin-wave demultiplexer enabling frequency-dependent separation of GHz signals. The device is based on two-dimensional magnon transport in the form of spin-wave beams in unpatterned magnetic nanosheets. The intrinsic frequency-dependence of the beam direction is exploited to realize a passive functioning obviating an external control and additional power consumption. This approach paves the way to magnonic multiplexing circuits enabling simultaneous information transport and processing.Comment: 16 pages, 3 figure