Influence of lipid composition on the thermotropic behavior and size distribution of mixed cationic liposomes

Cationic liposomes are studied mainly as nonviral nucleic acid delivery systems and to a lesser extent as carriers/adjuvants of vaccines and as low-molecular-weight drug carriers. It is well established that the performance and the biological activity of liposomes in general are strongly related to their physicochemical properties. We investigated the thermotropic behavior and the size distribution of mixed cationic liposomes formulated with different percentages of 1,2 dimyristoyl-sn-glycero-3-phosphatidylcholine and one of four cationic amphiphiles characterized by a pyrrolidinium headgroup with the aim of achieving a better understanding of how the molecular structure of the cationic amphiphile and its mole percentage affect the physicochemical properties of the liposomes. Multilamellar vesicles and large unilamellar vesicles were studied by differential scanning calorimetry and turbidity, respectively, to characterize the thermotropic behavior and lipid phase, whereas dynamic light scattering was used to determine size distribution. This study shows that subtle modifications in the cationic amphiphile's molecular structure and in liposome composition may have dramatic effects on the organization of the liposome bilayer and hence on the morphological and physicochemical features of the liposomes, thus being highly relevant to the biological features investigated previously.     

Reverse-flow adsorption for process-integrated recycling of homogeneous transition-metal catalysts

Supramolecular strategies, based on hydrogen bonds and ionic interactions, were investigated as tools for the recovery and recycling of homogeneous transition-metal catalysts by using reverse-flow adsorption (RFA) technology. The association (in solution) and adsorption (on support) of new functionalized host materials and phosphine guest ligands, functionalized with the complementary binding motifs, were fine-tuned for the application of these materials in a RFA reactor. The RFA technology for process-integrated recycling of homogeneous catalysts using these tailor-made phosphine ligands and silica-supported host materials resulted in a stable, semicontinuous catalytic system. Rhodium-catalyzed asymmetric hydrogenation of methyl acetamidoacrylate and asymmetric hydrosilylation of acetophenone were studied as test reactions. Depending on the catalytic process the metal complex could be recycled several times without significant loss in conversion.     

Enhanced imaging of magnetic structures in micropatterned arrays of Co dots and antidots

A specific technique of numerical treatment of atomic force microscopy (AFM) and magnetic force microscopy (MFM) signal has been developed to enhance the quality of raw images, in order both to improve their contrast and to gain better insight on the sample topography and on the local arrangement of the magnetisation vector. Basically, the technique consists in computing the optimum conformal transformation that allows one to superimpose two AFM images of the same area, acquired performing subsequent scans whose fast scan axis were mutually perpendicular, and applying the inverse transform to the second image. After MFM image superposition, the two datasets were either summed or subtracted, in order to improve the magnetic contrast. Computations have been done in a Matlab^® workspace with the help of Image Processing Toolbox 4.2. Improved MFM images obtained on both dots and antidots thin evaporated Co arrays in the demagnetised state (after performing alternate field demagnetisation parallel and perpendicular to the array plane) have been interpreted. Samples consisting of large-size patterns (1×1 mm) of circular dots/antidots with square/hexagonal lattices and minimum diameters of 1 μm were prepared by optical lithography. The magnetic film thickness was chosen depending on resist thickness, and varied between 25 and 150 nm, with a fixed ratio 1:4 between metal/resist film thickness. MFM was exploited to obtain images of either intra-dot or inter-antidot magnetic structures.     

Structural preablation dynamics of graphite observed by ultrafast electron crystallography

By means of time-resolved electron crystallography, we report direct observation of the structural dynamics of graphite, providing new insights into the processes involving coherent lattice motions and ultrafast graphene ablation. When graphite is excited by an ultrashort laser pulse, the excited carriers reach their equilibrium in less then one picosecond by transferring heat to a subset of strongly coupled optical phonons. The time-resolved diffraction data show that on such a time scale the crystal undergoes a contraction whose velocity depends on the excitation fluence. The contraction is followed by a large expansion which, at sufficiently high fluence, leads to the ablation of entire graphene layers, as recently predicted theoretically.     

Theory of ground state factorization in quantum cooperative systems

We introduce a general analytic approach to the study of factorization points and factorized ground states in quantum cooperative systems. The method allows us to determine rigorously the existence, location, and exact form of separable ground states in a large variety of, generally nonexactly solvable, spin models belonging to different universality classes. The theory applies to translationally invariant systems, irrespective of spatial dimensionality, and for spin-spin interactions of arbitrary range.     

Geometric scaling from Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution

We show that the geometric scaling of the total virtual photon-proton cross section data can be explained using standard linear Dokshitzer-Gribov-Altarelli-Parisi perturbative evolution with generic boundary conditions in a wide kinematic region. This allows us to single out the region where geometric scaling may provide evidence for parton saturation.     

Multimodal imaging: an evaluation of univariate and multivariate methods for simultaneous EEG/fMRI

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has been proposed as a tool to study brain dynamics with both high temporal and high spatial resolution. Multimodal imaging techniques rely on the assumption of a common neuronal source for the different recorded signals. In order to maximally exploit the combination of these techniques, one needs to understand the coupling (i.e., the relation) between electroencephalographic (EEG) and fMRI blood oxygen level-dependent (BOLD) signals.     

The double-soft integral for an arbitrary angle between hard radiators

We consider the double-soft limit of a generic QCD process involving massless partons and integrate analytically the double-soft eikonal functions over the phase-space of soft partons (gluons or quarks) allowing for an arbitrary relative angle between the three-momenta of two hard massless radiators. This result provides one of the missing ingredients for a fully analytic formulation of the nested soft-collinear subtraction scheme described in Caola et al. (Eur Phys J C 77(4):248, 2017).     

Photoexcitation in two-dimensional topological insulators

One of the most fascinating challenges in Physics is the realization of an electron-based counterpart of quantum optics, which requires the capability to generate and control single electron wave packets. The edge states of quantum spin Hall (QSH) systems, i.e., two-dimensional (2D) topological insulators realized in HgTe/CdTe and InAs/GaSb quantum wells, may turn the tide in the field, as they do not require the magnetic field that limits the implementations based on quantum Hall effect. However, the band structure of these topological states, described by a massless Dirac fermion Hamiltonian, prevents electron photoexcitation via the customary vertical electric dipole transitions of conventional optoelectronics. So far, proposals to overcome this problem are based on magnetic dipole transitions induced via Zeeman coupling by circularly polarised radiation, and are limited by the g-factor. Alternatively, optical transitions can be induced from the edge states to the bulk states, which are not topologically protected though.Here we show that an electric pulse, localized in space and/or time and applied at a QSH edge, can photoexcite electron wavepackets by intra-branch electrical transitions, without invoking the bulk states or the Zeeman coupling. Such wavepackets are spin-polarised and propagate in opposite directions, with a density profile that is independent of the initial equilibrium temperature and that does not exhibit dispersion, as a result of the linearity of the spectrum and of the chiral anomaly characterising massless Dirac electrons. We also investigate the photoexcited energy distribution and show how, under appropriate circumstances, minimal excitations (Levitons) are generated. Furthermore, we show that the presence of a Rashba spin–orbit coupling can be exploited to tailor the shape of photoexcited wavepackets. Possible experimental realizations are also discussed.     

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.