•Adsorption is an effective technique to remove contaminants from gas stream.•Recent review on removal of harmful contaminants, I2, Kr and Xe at reprocessing condition.•Porous solid sorbents has ...several advantages for capture of volatile gases.•I2, Kr and Xe removal capacity of different sorbents are reported.•MOFs are also effective sorbents for capture iodine and krypton.
Nuclear energy production is growing rapidly worldwide to satisfy increasing energy demands. Reprocessing of used nuclear fuel (UNF) is expected to play an important role for sustainable development of nuclear energy by increasing the energy extracted from the fuel and reducing the generation of the high level waste (HLW). However, during the reprocessing of used nuclear fuel (UNF) gaseous radioactive nuclides including iodine, krypton, xenon, carbon, and tritium are released into the atmosphere through off-gas streams. The volatile iodine (129I), and krypton (85Kr) gases have long lived-isotopes; which have adverse effects on the environment as well as human health. Consequently, the capture of these two target radionuclides (species) is essential for the enhanced growth of nuclear energy. In this review we discuss several techniques for capture of volatile contaminants iodine, krypton, and xenon, focusing upon adsorption using solid sorbents, which has shown promising results for more than 70years. Commonly used and recently developed sorbents are summarized in this article along with a short review of the results. Metal-organic-frameworks (MOFs), gaining favor in recent years as sorbents for the capture of off-gas contaminants are also discussed. Finally, some considerations of future trends and prospects for investigations of the capture of volatile radionuclides are presented.
A framework is developed for inference concerning the covariance operator of a functional random process, where the covariance operator itself is an object of interest for statistical analysis. ...Distances for comparing positive-definite covariance matrices are either extended or shown to be inapplicable to functional data. In particular, an infinite-dimensional analogue of the Procrustes size-and-shape distance is developed. Convergence of finite-dimensional approximations to the infinite-dimensional distance metrics is also shown. For inference, a Fréchet estimator of both the covariance operator itself and the average covariance operator is introduced. A permutation procedure to test the equality of the covariance operators between two groups is also considered. Additionally, the use of such distances for extrapolation to make predictions is explored. As an example of the proposed methodology, the use of covariance operators has been suggested in a philological study of cross-linguistic dependence as a way to incorporate quantitative phonetic information. It is shown that distances between languages derived from phonetic covariance functions can provide insight into the relationships between the Romance languages.
The link between brain amyloid-β (Aβ), metabolism, and dementia symptoms remains a pressing question in Alzheimer's disease. Here, using positron emission tomography (
Fflorbetapir tracer for Aβ and
...FFDG tracer for glucose metabolism) with a novel analytical framework, we found that Aβ aggregation within the brain's default mode network leads to regional hypometabolism in distant but functionally connected brain regions. Moreover, we found that an interaction between this hypometabolism with overlapping Aβ aggregation is associated with subsequent cognitive decline. These results were also observed in transgenic Aβ rats that do not form neurofibrillary tangles, which support these findings as an independent mechanism of cognitive deterioration. These results suggest a model in which distant Aβ induces regional metabolic vulnerability, whereas the interaction between local Aβ with a vulnerable environment drives the clinical progression of dementia.
A new technique for the synthesis of large sheets (>10
cm
2) of multi-layered graphene is presented. The condensation onto a heated surface (≈650
°C) of fumes from the thermal decomposition of ...asphalt in a ceramic crucible produces carbon films with a metallic sheen. Heating was done by a Fisher burner (natural gas/air) flame and the crucible was covered but exposed to laboratory atmosphere. These films were determined to be multi-layered graphene by scanning electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy (XPS), Raman and infrared spectroscopy and X-ray diffraction. XPS indicates that the films are primarily sp
2 hybridized carbon with small amounts of sp
3 C–H and C–O or C–N functionalities. Based on the D band shift (1593
cm
−1) and the ratio of D band to G band (1354
cm
−1) of 0.93, the Raman spectrum also indicates that the material is sp
2 C with some nanocrystalline features. The infrared spectrum exhibits A
1U (868
cm
−1) and E
1U (1599
cm
−1) stretching of the intralayer bonds of graphene. This form of chemical vapor deposition may be a scalable to give much larger surface areas. Furthermore, the process does not require metal substrates. Deposition onto silica nanosprings and diatomites is demonstrated.
Three methods of measuring coffee roast degree were compared using titratable acidity as an indicator of roast-dependent flavor change. The first roast degree method was based on prediction of the ...cracks with online near infrared spectroscopy and partial least squares regression, the second was based on changes in online near infrared absorbance, and the third was the common L* value from the CIELAB color space in the visible spectrum. Roasting trials utilized arabica coffee from eight origins in an air roaster, and results demonstrated the superiority of an online near infrared sensor for real-time roast degree measurement. A second dataset with constant temperature roasts showed how acidity can be controlled by changing both the roasting temperature and roast degree, finding the linear effects of roast time and roast degree on acidity.
•Sorption of radioactive iodine and krypton on C@ETS-10 sorbent using continuous column.•Multicomponent experiments were performed to investigate sorption capacity of the sorbent for iodine and ...krypton.•Sorption of iodine on sorbent was confirmed by EDS and XPS spectra.•Langmuir and Freundlich models were fitted for iodine and krypton contaminants.•C@ETS-10 was found to be remarkable sorbent for adsorption of iodine and krypton from the gas stream.
A novel Engelhard Titanosilicate – 10 (ETS-10) supported 10wt% hollow carbon nano-polyhedron (10wt% C@ETS-10) sorbent developed in our laboratory was investigated for adsorption of the radioactive iodine and krypton from off-gas stream using a continuous flow adsorption column. Adsorption experiments were performed to determine the capacity of 10wt% C@ETS-10 sorbent for iodine and krypton in multicomponent mixture system by varying operating parameters, such as inlet concentration of iodine (I2) and krypton (Kr), and adsorption column temperature. Pristine and used sorbents were characterized by scanning electron microscopy-energy dispersion spectroscopy (SEM-EDS), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy to identify the morphology, elemental and vibration analysis of the sorbent before and after the experiments. EDS and XPS spectra of the used samples clearly indicate the presence of iodine on the sorbent. Multicomponent sorption capacities of I2 and Kr of 10wt% C@ETS-10 sorbent calculated from the breakthrough curves at 20°C at 25ppm I2 and 70ppm Kr balanced with nitrogen were found to be 41.5 and 0.0323mgg−1, respectively. Sorption data was found to be best fitted by the Langmuir as well as Freundlich isotherm model. Experimental data were analyzed by Thomas, Yoon-Nelson, and Bohart-Adams sorption kinetics models to predict the breakthrough curves and calculate the characteristic parameters of the column that are useful for process design for the multicomponent system. Results show that 10wt% C@ETS-10 sorbent has potential sorbent for adsorption of multicomponent (I2 and Kr) from off-gas stream.
The total phenolic contents and antioxidant activities of garlics from California, Oregon, Washington, and New York were determined by Fourier transform infrared (FT-IR) spectroscopy (400–4000 cm–1). ...The total phenolic content was quantified Folin–Ciocalteu assay (FC) and three antioxidant activity assays, 2,2-diphenyl-picrylhydrazyl (DPPH) assay, Trolox equivalent antioxidant capacity (TEAC) assay, and ferric reducing antioxidant power (FRAP), were employed for reference measurements. Four independent partial least-squares regression (PLSR) models were constructed with spectra from 25 extracts and their corresponding FC, DPPH, TEAC, and FRAP with values for 20 additional extracts predicted (R > 0.95). The standard errors of calibration and standard error of cross-validation were <1.45 (TEAC), 0.36 (FRAP), and 0.33 μmol Trolox/g FW (DPPH) and 0.55 mg gallic acid/g FW (FC). Cluster and dendrogram analyses could segregate garlic grown at different locations. Hydroxyl and phenolic functional groups most closely correlated with garlic antioxidant activity.
A lateral flow test strip assay, enabling sensitive detection of DNA specific to the foodborne pathogen E. coli O157:H7, is described. The use of LNA-conjugated gold nanoparticle probes, along with ...signal amplification protocols, results in minimum detectable concentrations of ~0.4 nM.
Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm), ...often in combination with a local search method (such as gradient descent) in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a potentially useful tool in the construction of biophysical neuron models.
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