Studying sulfur functional groups in Norway spruce year rings using S L-edge total electron yield spectroscopy

Profiles of the major sulfur functional groups in mature Norway spruce wood tissue have been established for the first time. The big challenge was the development of a method suitable for sulfur speciation in samples with very low sulfur content (<100 ppm). This became possible by synchrotron X-ray absorption spectroscopy at the sulfur L-edge in total electron yield (TEY) detection mode with thin gold-coated wood slices. Functional groups were identified using sulfur compound spectra as fingerprints. Latewood of single year rings revealed metabolic plausible sulfur forms, particularly inorganic sulfide, organic disulfide, methylthiol, and highly oxidized sulfur. Form-specific profiles with Norway spruces from three different Swiss forest sites revealed high, but hitherto little-noticed, sulfur intensities attributable to natural heartwood formation and a common, but physiologically unexpected maximum around year ring 1986 with trees from the industrialized Swiss Plateau. It is hypothesized whether it may have resulted from the huge reduction in sulfur emissions after 1980 due to Swiss policy. Comparison with total S content profiles from optical emission spectroscopy underlined the more accurate and temporally better resolved TEY data with single wood year rings and it opened novel insights into the wood cell chemistry.     

Bifurcation analysis in a silicon neuron

In this paper, we describe an analysis of the nonlinear dynamical phenomenon associated with a silicon neuron. Our silicon neuron in Very Large Scale Integration (VLSI) integrates Hodgkin?CHuxley (HH) model formalism, including the membrane voltage dependency of temporal dynamics. Analysis of the bifurcation conditions allow us to identify different regimes in the parameter space that are desirable for biasing our silicon neuron. This approach of studying bifurcations is useful because it is believed that computational properties of neurons are based on the bifurcations exhibited by these dynamical systems in response to some changing stimulus. We describe numerical simulations of the Hopf bifurcation which is characteristic of class 2 excitability in the HH model. We also show experimental measurements of an observed phenomenon in biological neurons and termed excitation block, firing rate and effect of current impulses. Hence, by showing that this silicon neuron has similar bifurcations to a certain class of biological neurons, we can claim that the silicon neuron can also perform similar computations.     

Influence of Aluminum Content in g-TiAl with L10 Structure during Ordering Processes

Based on EAM (embedded atom method) interatomic potential, the effect of aluminum content on the type of order-disorder transformation (ODT) and the structure properties (lattice constants, volume, c/a ratio and configuration energy) during ordering processes was investigated for g-TiAl based alloys. Results show that for the alloys with lower than 50%Al (all composition is in atom number fraction), the ODT is the first order transition, and the second order transition for the alloys with equal or higher than 50% Al. The increase of aluminum content results in the critical temperature increasing. The aluminum content has a very little effect on the lattice constants, the volume and the c/a ratio, but has a significant effect on the configuration energy. A metastable disordered state was found for the alloys with less than 50%Al.     

Bayesian hemodynamic parameter estimation by bolus tracking perfusion weighted imaging

A delay-insensitive probabilistic method for estimating hemodynamic parameters, delays, theoretical residue functions, and concentration time curves by computed tomography (CT) and magnetic resonance (MR) perfusion weighted imaging is presented. Only a mild stationarity hypothesis is made beyond the standard perfusion model. New microvascular parameters with simple hemodynamic interpretation are naturally introduced. Simulations on standard digital phantoms show that the method outperforms the oscillating singular value decomposition (oSVD) method in terms of goodness-of-fit, linearity, statistical and systematic errors on all parameters, especially at low signal-to-noise ratios (SNRs). Delay is always estimated sharply with user-supplied resolution and is purely arterial, by contrast to oSVD time-to-maximum TMAX that is very noisy and biased by mean transit time (MTT), blood volume, and SNR. Residue functions and signals estimates do not suffer overfitting anymore. One CT acute stroke case confirms simulation results and highlights the ability of the method to reliably estimate MTT when SNR is low. Delays look promising for delineating the arterial occlusion territory and collateral circulation.     

Biomimetic neural network for modifying biological dynamics during hybrid experiments

Electrical stimulation of nerve tissue and recording of neural electrical activity are the basis of emerging prostheses and treatments for many neurological disorders. Here we present closed-loop bio-hybrid experiment using in vitro biological neuronal network (BNN) with an artificial neural network (ANN) implemented in a neuromorphic board. We adopted a neuromorphic board which is able to perform real-time event detection and trigger an electrical stimulation of the BNN. This system embeds an ANN, based on Izhikevich neurons which can be put in uni- and bi-directional communication with the BNN. The ANN used in the following experiments was made up of 20 excitatory neurons with inhibition synapse and with synaptic plasticity to design central pattern generator. Open-loop and closed-loop hybrid experiments show that the biological dynamics can be modified. This work can be seen as the first step towards the realization of an innovative neuroprosthesis.     

Tangential momemtum accommodation in microtube

Experimental investigations of isothermal steady flows for various gases have been carried out in a silica micro tube. This study is focused on the mass flow rate measurements of these flows in slip regime using a suitable powerful platform. First we analyse, for each gas, the pertinence of a first or second order continuum treatment; then we deduce from experiments, using the appropriate treatment, the tangential momentum accommodation coefficient (TMAC) of each gas. The TMAC obtained for the various pairs of gas (nitrogen, argon, helium)/surface (fused silica) exclude a full diffuse reflection.     

Biomimetic microfluidic neurons for bio-hybrid experiments

Millions of people worldwide have incurable and debilitating conditions called neurodegenerative diseases that influence one’s cognitive and/or motor functions. There is currently an increasing number of neuroprosthesis, but they have power consumption and bio-compatibility issues. To bring neuroprosthesis into realization and for future long-term replacement of damaged brain areas with artificial devices, understanding of neurophysiological behaviors and investigations on the interaction of neuronal cell assemblies is essential. To circumvent the limitations, in this article we propose a biomimetic artificial neuron to mimic and/or to replace the biological neurons. This biomimetic neuron is based on microfluidic technique with ionic exchange capable of performing bio-hybrid experiments.     

SERS detection of biomolecules using lithographed nanoparticles towards a reproducible SERS biosensor

In this paper we highlight the accurate spectral detection of bovine serum albumin and ribonuclease-A using a surface-enhanced Raman scattering (SERS) substrate based on gold nanocylinders obtained by electron-beam lithography (EBL). The nanocylinders have diameters from 100 to 180 nm with a gap of 200 nm. We demonstrate that optimizing the size and the shape of the lithographed gold nanocylinders, we can obtain SERS spectra of proteins at low concentration. This SERS study enabled us to estimate high enhancement factors (10(5) for BSA and 10(7) for RNase-A) of important bands in the protein Raman spectrum measured for 1 mM concentration. We demonstrate that, to reach the highest enhancement, it is necessary to optimize the SERS signal and that the main parameter of optimization is the LSPR position. The LSPR have to be suitably located between the laser excitation wavelength, which is 632.8 nm, and the position of the considered Raman band. Our study underlines the efficiency of gold nanocylinder arrays in the spectral detection of proteins.