Thermophysical Properties of Amino Acid-Based Ionic Liquids

Ionic liquids (ILs) having either cations or anions derived from naturally occurring amino acids have been synthesized and characterized as amino acid-based ionic liquids (AAILs) In this work, the experimental measurements of the temperature dependence or density. viscosity, heat capacity, and thermal conductivity of several AAILs, namely, tributylmethylammonium serinate ([N-444][Ser], tributylmethylammonium taurmate ([N-444][Tau]) tributylmethylammonium lysinate a [N-444][ Lys]), tributylmethylammonium threonate ([N-444][Thr]), tetrabutylphosphonium serinate ([P-4444][Ser]), tetrabutylphosphonium taurmate ([P-4444][Tau]), tetrabutylphosphonium lysinate ([P-4444][Lys]), tetrabutylphosphonium threonate P-4444 Thr tetrabutylphosphonium prolinate P-4444 ((Pro(), tetrabutylphosphonium valinate ([P-4444][Val]), and tetrabutylphosphonium cysteinate ([P-4444][Cys]), are presented The influence of cations and anions on studied properties is discussed. On the basis of experimental data. the QSPR (quantitative structure property relationship) correlations and group contribution methods for thermophysical properties of AAILs have been developed, which form the basis for the development of the computer-aided molecular design (CAMD) of AAILs It has also been demonstrated that that the predictive data obtained by con elation methods ale in good agreement with the experimental data The correlations developed, herein. can thus be used to evaluate the studied thermophysical properties of AAILs for use in process design or in the CAMD of new AAILs

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Intellectual Property management in publicly funded R&D centres—A comparison of university-based and company-based research centres

Recent thinking on open innovation and the knowledge-based economy have stressed the importance of external knowledge sources in stimulating innovation. Policy-makers have recognised this, establishing publicly funded Centres of R&D Excellence with the objective of stimulating industry–science links and localised innovation spillovers. Here, we examine the contrasting IP management practices of a group of 18 university- and company-based R&D centres supported by the same regional programme. Our analysis covers all but one of the Centres supported by the programme and suggests marked contrasts between the IP strategies of the university-based and company-based centres. This suggests the potential for very different types of knowledge spillovers from publicly funded R&D centres based in different types of organisations, and a range of alternative policy approaches to the future funding of R&D centres depending on policy-makers’ objectives.

Combined R-matrix eigenstate basis set and finite-difference propagation method for the time-dependent Schrodinger equation: The one-electron case

In this work we present the theoretical framework for the solution of the time-dependent Schrödinger equation (TDSE) of atomic and molecular systems under strong electromagnetic fields with the configuration space of the electron’s coordinates separated over two regions; that is, regions I and II. In region I the solution of the TDSE is obtained by an R-matrix basis set representation of the time-dependent wave function. In region II a grid representation of the wave function is considered and propagation in space and time is obtained through the finite-difference method. With this, a combination of basis set and grid methods is put forward for tackling multiregion time-dependent problems. In both regions, a high-order explicit scheme is employed for the time propagation. While, in a purely hydrogenic system no approximation is involved due to this separation, in multielectron systems the validity and the usefulness of the present method relies on the basic assumption of R-matrix theory, namely, that beyond a certain distance (encompassing region I) a single ejected electron is distinguishable from the other electrons of the multielectron system and evolves there (region II) effectively as a one-electron system. The method is developed in detail for single active electron systems and applied to the exemplar case of the hydrogen atom in an intense laser field.

Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders

Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of

Ambiguity, social opinion and the use of common property resources

In this paper we argue that ambiguity, combined with social opinion formation, can be used as the foundation of a game-theoretic equilibrium concept that transcends the standard Nash equilibrium concept, applied to a model of the tragedy of the commons. Our approach sheds light on the international environmental crisis and the relevant ongoing international negotiations. We conclude that social opinion formation in most cases has a significant impact on equilibrium common property resource usage.

Structural basis for the platelet-collagen interaction - The smallest motif within collagen that recognizes and activates platelet glycoprotein VI contains two glycine-proline-hydroxyproline triplets

Collagen-related peptide is a selective agonist for the platelet collagen receptor Glycoprotein VI. The triple helical peptide contains ten GPO triplets/strand (single letter amino acid nomenclature, where O is hydroxyproline) and so over-represents GPO compared with native collagen sequence. To investigate the ability of Glycoprotein VI to recognize GPO triplets in a setting more representative of the collagens, we synthesized a set of triple helical peptides containing fewer GPO triplets, varying their number and spacing within an inert (GPP)(n) backbone. The adhesion of recombinant human Glycoprotein VI ectodomain, like that of human platelets, to these peptides increased with their GPO content, and platelet adhesion was abolished by the specific anti-Glycoprotein VI-blocking antibody, 10B12. Platelet aggregation and protein tyrosine phosphorylation were induced only by cross-linked peptides and only those that contained two or more GPO triplets. Such peptides were less potent than cross-linked collagen-related peptide. Our data suggest that both the sequences GPOGPO and GPO center dot center dot center dot center dot center dot center dot center dot center dot center dot GPO represent functional Glycoprotein VI recognition motifs within collagen. Furthermore, we propose that the (GPO)(4) motif can support simultaneous binding of two glycoprotein VI molecules, in either a parallel or anti-parallel stacking arrangement, which could play an important role in activation of signaling.

High-velocity features: A ubiquitous property of Type Ia supernovae

Evidence of high-velocity features (HVFs) such as those seen in the near-maximum spectra of some Type Ia supernovae (SNe Ia; e. g., SN 2000cx) has been searched for in the available SN Ia spectra observed earlier than 1 week before B maximum. Recent observational efforts have doubled the number of SNe Ia with very early spectra. Remarkably, all SNe Ia with early data ( seven in our Research Training Network sample and 10 from other programs) show signs of such features, to a greater or lesser degree, in Ca II IR and some also in the Si II lambda 6355 line. HVFs may be interpreted as abundance or density enhancements. Abundance enhancements would imply an outer region dominated by Si and Ca. Density enhancements may result from the sweeping up of circumstellar material (CSM) by the highest velocity SN ejecta. In this scenario, the high incidence of HVFs suggests that a thick disk and/or a high-density companion wind surrounds the exploding white dwarf, as may be the case in single degenerate systems. Large-scale angular fluctuations in the radial density and abundance distribution may also be responsible: this could originate in the explosion and would suggest a deflagration as the more likely explosion mechanism. CSM interaction and surface fluctuations may coexist, possibly leaving different signatures on the spectrum. In some SNe, the HVFs are narrowly confined in velocity, suggesting the ejection of blobs of burned material.