Radiation crosslinked polyvinyl alcohol/polyvinyl pyrrolidone/acrylic acid hydrogels: swelling,crosslinking and dye adsorption study

Iranian Polymer Journal - Hydrogels were produced from mixtures of polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP), and acrylic acid (AAc) using γ-radiation at doses of 3, 7, and...     

Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application

Many hydrologic phenomena and applications such as drought, flood, irrigation management and scheduling needs high resolution satellite soil moisture data at a local/regional scale. Downscaling is a very important process to convert a coarse domain satellite data to a finer spatial resolution. Three artificial intelligence techniques along with the generalized linear model (GLM) are used to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) derived soil moisture, which is currently available at a very coarse scale of ~40 Km. Artificial neural network (ANN), support vector machine, relevance vector machine and generalized linear models are chosen for this study to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) with the SMOS derived soil moisture. Soil moisture deficit (SMD) derived from a hydrological model called PDM (Probability Distribution Model) is used for the downscaling performance evaluation. The statistical evaluation has also been made with the day-time and night-time MODIS LST differences with the mean day and night-time PDM SMD data for the selection of effective MODIS products. The accuracy and robustness of all the downscaling algorithms are discussed in terms of their assumptions and applicability. The statistical performance indices such as R ² , %Bias and RMSE indicates that the ANN (R ² ? =?0.751, %Bias?=??0.628 and RMSE?=?0.011), RVM (R ² ? =?0.691, %Bias?=?1.009 and RMSE?=?0.013), SVM (R ² ? =?0.698, %Bias?=?2.370 and RMSE?=?0.013) and GLM (R ² ? =?0.698, %Bias?=?1.009 and RMSE?=?0.013) algorithms on the whole are relatively more skillful to downscale the variability of the soil moisture in comparison to the non-downscaled data (R ² ? =?0.418 and RMSE?=?0.017) with the outperformance of ANN algorithm. The other attempts related to growing and non-growing seasons have been used in this study to reveal that season based downscaling is even better than continuous time series with fairly high performance statistics.     

Parallelized path-based search for constraint satisfaction in autonomous cognitive agents

The Journal of Supercomputing - Cognitive agents are typically utilized in autonomous systems for automated decision making. With the widespread use of autonomous systems in complex environments,...     

Effect of NR and EPDM on the rheology of HDPE/PP blends

Summary We studied melt-rheological properties of ternary blends of polypropylene and high-density polyethylene with an elastomer (natural rubber or ethylene-propylene-diene), at several blending ratios and shear rates. Measurements made on a cone-plate rheometer are presented and discussed as a function of blend composition. The effect of the shear rate on the viscosity and flow curve is discussed in terms of the exponent of the power low for a non-Newtonian liquid. The addition of an elastomer to the polyolefins blends changes the shape of the viscosity-composition curve; this change is discussed in terms of the possible morphology of the blend. Received: 25 September 1998/Revised version: 8 February 1999/Accepted: 9 February 1999     

Sections-based bibliographic coupling for research paper recommendation

Scientometrics - Digital libraries suffer from the problem of information overload due to immense proliferation of research papers in journals and conference papers. This makes it challenging for...     

NOx formation in post-flame gases from syngas/air combustion at atmospheric pressure

Species concentration measurements specifically those associated with nitrogen oxides (NO_x) can act as important validation targets for developing kinetic models to predict NO_x emissions under syngas combustion accurately. In the present study, premixed combustion of syngas/air mixtures, with equivalence ratio (Φ) from 0.5 to 1.0 and H₂/CO ratio from 0.25 to 1.0 was conducted in a McKenna burner operating at atmospheric pressure. Temperature and NO_x concentrations were measured in the post-combustion zone. For a given H₂/CO ratio, increasing the equivalence ratio from lean to stoichiometric resulted in an increase in NO and decrease in NO₂ concentration near the flame. Increasing the H₂/CO ratio led to a decrease in the temperature as well as the NO concentration near the flame. Based on the axial profiles above the burner, NO concentration increases right above the flame while NO₂ concentration decreases through NO₂-NO conversion reactions according to the path flux analysis. In addition, the present experiments were operated in the laminar region where multidimensional transport effects play significant roles. In order to account for the radial and axial diffusive and convective coupling to chemical kinetics in laminar flow, a multidimensional model was developed to simulate the post-combustion species and temperature distribution. The measurements were compared against both multidimensional computational fluid dynamics (CFD) simulations and one-dimensional burner-stabilized flame simulations. The multidimensional model predictions resulted in a better agreement with the measurements, clearly highlighting the effect of multidimensional transport.     

Electrochemical properties of titanium arsenate membrane

Membrane potential is a measurable and reliable parameter to characterize the charge property of membrane. Membrane potentials have been measured across polystyrene based titanium arsenate membrane separating various 1:1 electrolytes at different concentrations. Membrane potential data have been used to calculate transference number of ions, mobility, distribution coefficient, charge effectiveness, permselectivity and also to derive the thermodynamically fixed charge density which is an important characteristic governing the membrane phenomena by utilizing the generally accepted theories for the salt concentration dependence of uni-univalent potentials, proposed by Teorell-Meyer-Sievers and Kobatake method and these are compared in order to obtain a relationship for the theoretical data of uni-univalent potentials. The good agreement between the theoretical and the experimental data of uni-univalent potentials proves the applicability of the relationship derived to the membrane system. Kobatake's equation was used under two limiting conditions, namely in the concentration range and in the dilute range. The two limiting forms of Kobatake's equation gave identical values of θ for the membrane taken in this investigation. Membrane is negatively charged (cation selective) and the selectivity increases with dilution. The structure of the membrane was observed with the aid of a scanning electron microscope. The order of fixed charge density for electrolytes used is found to be KCl > NaCl > LiCl.     

Stand-off detection of solid targets with diffuse reflection spectroscopy using a high-power mid-infrared supercontinuum source

We measure the diffuse reflection spectrum of solid samples such as explosives (TNT, RDX, PETN), fertilizers (ammonium nitrate, urea), and paints (automotive and military grade) at a stand-off distance of 5 m using a mid-infrared supercontinuum light source with 3.9 W average output power. The output spectrum extends from 750-4300 nm, and it is generated by nonlinear spectral broadening in a 9 m long fluoride fiber pumped by high peak power pulses from a dual-stage erbium-ytterbium fiber amplifier operating at 1543 nm. The samples are distinguished using unique spectral signatures that are attributed to the molecular vibrations of the constituents. Signal-to-noise ratio (SNR) calculations demonstrate the feasibility of increasing the stand-off distance from 5 to ~150 m, with a corresponding drop in SNR from 28 to 10 dB.     

Evaluation of <Emphasis Type="Italic">h</Emphasis>-index,its variants and extensions based on publication age &amp; citation intensity in civil engineering

The scientific community has proposed diversified set of parameters to rank researchers, including publications, citations, h-index, different variants and extensions of h-index. However, there is a debate in the scientific Community which index ranks authors in a better way. Current state-of-the-art depicts that these indices are evaluated on imaginary case scenarios and small datasets. Furthermore, these indices are evaluated on different datasets, making it difficult to grasp the contribution and importance of each index over the others. To analyze the individual behavior of each index, these indices should comprehensively be evaluated on some extensive data set. This study emphasizes on the scrutiny of h-index, some of its variants and extensions to rank authors. These indices are evaluated using a comprehensive data set of Civil Engineering field. For the evaluation of results obtained from these indices, first correlation was calculated among indices. There exists weak correlation between various indices, which demonstrates that the author’s rankings acquired from these indices are not identical. Secondly, occurrences of awardees are checked in all ranked lists. The prestigious award winners of four Civil Engineering societies are considered as a benchmark. In top 10% of ranked list, maximum 47% of the awardees were brought by Wu-index. Overall, none of the index succeeded in bringing 100% awardees to the top rankings. Highest number of awardees on top of all ranked lists are found to be from ACI (American Concrete Institute), which shows ACI might be dependent on these indices for its criterion to honor awards.