Cubic optical nonlinearity of free electrons in bulk gold

A fast (τresponse &lt;90 fs) free-electron spin-flipping frequency-degenerate nonlinearity with a significant value of |χ(3)xxyy(ω,ω,ω,-ω) χ(3)xyyx(ω,ω,ω,-ω)| ~ 10-8 esu has been observed in bulk gold at 1260 nm by use of a new pump-probe polarization-sensitive technique. <br/

Landau damping in thin films irradiated by a strong laser field

The rate of linear collisionless damping (Landau damping) in a classical electron gas confined to a heated ionized thin film is calculated. The general expression for the imaginary part of the dielectric tensor in terms of the parameters of the single-particle self-consistent electron potential is obtained. For the case of a deep rectangular well, it is explicitly calculated as a function of the electron temperature in the two limiting cases of specular and diffuse reflection of the electrons from the boundary of the self-consistent potential. For realistic experimental parameters, the contribution of Landau damping to the heating of the electron subsystem is estimated. It is shown that for films with a thickness below about 100 nm and for moderate laser intensities it may be comparable with or even dominate over electron-ion collisions and inner ionization.Comment: 15 pages, 2 figure

Size-Dependent Surface Plasmon Dynamics in Metal Nanoparticles

We study the effect of Coulomb correlations on the ultrafast optical dynamics of small metal particles. We demonstrate that a surface-induced dynamical screening of the electron-electron interactions leads to quasiparticle scattering with collective surface excitations. In noble-metal nanoparticles, it results in an interband resonant scattering of d-holes with surface plasmons. We show that this size-dependent many-body effect manifests itself in the differential absorption dynamics for frequencies close to the surface plasmon resonance. In particular, our self-consistent calculations reveal a strong frequency dependence of the relaxation, in agreement with recent femtosecond pump-probe experiments.Comment: 8 pages + 4 figures, final version accepted to PR

Size-dependent Correlation Effects in Ultrafast Optical Dynamics of Metal Nanoparticles

We study the role of collective surface excitations in the electron relaxation in small metal particles. We show that the dynamically screened electron-electron interaction in a nanoparticle contains a size-dependent correction induced by the surface. This leads to new channels of quasiparticle scattering accompanied by the emission of surface collective excitations. We calculate the energy and temperature dependence of the corresponding rates, which depend strongly on the nanoparticle size. We show that the surface-plasmon-mediated scattering rate of a conduction electron increases with energy, in contrast to that mediated by a bulk plasmon. In noble-metal particles, we find that the dipole collective excitations (surface plasmons) mediate a resonant scattering of d-holes to the conduction band. We study the role of the latter effect in the ultrafast optical dynamics of small nanoparticles and show that, with decreasing nanoparticle size, it leads to a drastic change in the differential absorption lineshape and a strong frequency dependence of the relaxation near the surface plasmon resonance. The experimental implications of our results in ultrafast pump-probe spectroscopy are also discussed.Comment: 29 pages including 6 figure

The Global Energy Transition: A Review of the Existing Literature

This chapter presents an overview of the existing literature on the geopolitics of the global energy transition. Notwithstanding its potentially re-defining role for international relations, this issue has, so far, not been analysed in a comprehensive manner but in a rather fragmented way. This chapter represents a useful summary to the state-of-the-art of knowledge in the field, and therefore a useful starting point for the book

An HDG Method for Dirichlet Boundary Control of Convection Dominated Diffusion PDE

We first propose a hybridizable discontinuous Galerkin (HDG) method to approximate the solution of a \emph{convection dominated} Dirichlet boundary control problem. Dirichlet boundary control problems and convection dominated problems are each very challenging numerically due to solutions with low regularity and sharp layers, respectively. Although there are some numerical analysis works in the literature on \emph{diffusion dominated} convection diffusion Dirichlet boundary control problems, we are not aware of any existing numerical analysis works for convection dominated boundary control problems. Moreover, the existing numerical analysis techniques for convection dominated PDEs are not directly applicable for the Dirichlet boundary control problem because of the low regularity solutions. In this work, we obtain an optimal a priori error estimate for the control under some conditions on the domain and the desired state. We also present some numerical experiments to illustrate the performance of the HDG method for convection dominated Dirichlet boundary control problems

Petri Nets with Fuzzy Logic (PNFL): Reverse Engineering and Parametrization

Background: The recent DREAM4 blind assessment provided a particularly realistic and challenging setting for network reverse engineering methods. The in silico part of DREAM4 solicited the inference of cycle-rich gene regulatory networks from heterogeneous, noisy expression data including time courses as well as knockout, knockdown and multifactorial perturbations. Methodology and Principal Findings: We inferred and parametrized simulation models based on Petri Nets with Fuzzy Logic (PNFL). This completely automated approach correctly reconstructed networks with cycles as well as oscillating network motifs. PNFL was evaluated as the best performer on DREAM4 in silico networks of size 10 with an area under the precision-recall curve (AUPR) of 81%. Besides topology, we inferred a range of additional mechanistic details with good reliability, e.g. distinguishing activation from inhibition as well as dependent from independent regulation. Our models also performed well on new experimental conditions such as double knockout mutations that were not included in the provided datasets. Conclusions: The inference of biological networks substantially benefits from methods that are expressive enough to deal with diverse datasets in a unified way. At the same time, overly complex approaches could generate multiple different models that explain the data equally well. PNFL appears to strike the balance between expressive power and complexity. This also applies to the intuitive representation of PNFL models combining a straightforward graphical notation with colloquial fuzzy parameters

RNA-Dependent Oligomerization of APOBEC3G Is Required for Restriction of HIV-1

The human cytidine deaminase APOBEC3G (A3G) is a potent inhibitor of retroviruses and transposable elements and is able to deaminate cytidines to uridines in single-stranded DNA replication intermediates. A3G contains two canonical cytidine deaminase domains (CDAs), of which only the C-terminal one is known to mediate cytidine deamination. By exploiting the crystal structure of the related tetrameric APOBEC2 (A2) protein, we identified residues within A3G that have the potential to mediate oligomerization of the protein. Using yeast two-hybrid assays, co-immunoprecipitation, and chemical crosslinking, we show that tyrosine-124 and tryptophan-127 within the enzymatically inactive N-terminal CDA domain mediate A3G oligomerization, and this coincides with packaging into HIV-1 virions. In addition to the importance of specific residues in A3G, oligomerization is also shown to be RNA-dependent. Homology modelling of A3G onto the A2 template structure indicates an accumulation of positive charge in a pocket formed by a putative dimer interface. Substitution of arginine residues at positions 24, 30, and 136 within this pocket resulted in reduced virus inhibition, virion packaging, and oligomerization. Consistent with RNA serving a central role in all these activities, the oligomerization-deficient A3G proteins associated less efficiently with several cellular RNA molecules. Accordingly, we propose that occupation of the positively charged pocket by RNA promotes A3G oligomerization, packaging into virions and antiviral function

Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size

Abstract Background Co-expression has been widely used to identify novel regulatory relationships using high throughput measurements, such as microarray and RNA-seq data. Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes. For large networks, simulated expression data usually consist of hundreds or thousands of profiles with different perturbations or knock-outs, which is uncommon in real experiments due to their cost and the amount of work required. Thus, the performances of co-expression network analysis methods on large co-expression networks consisting of a few thousand nodes, with only a small number of profiles with a single perturbation, which more accurately reflect normal experimental conditions, are generally uncharacterized and unknown. Methods We proposed a novel network inference methods based on Relevance Low order Partial Correlation (RLowPC). RLowPC method uses a two-step approach to select on the high-confidence edges first by reducing the search space by only picking the top ranked genes from an intial partial correlation analysis and, then computes the partial correlations in the confined search space by only removing the linear dependencies from the shared neighbours, largely ignoring the genes showing lower association. Results We selected six co-expression-based methods with good performance in evaluation studies from the literature: Partial correlation, PCIT, ARACNE, MRNET, MRNETB and CLR. The evaluation of these methods was carried out on simulated time-series data with various network sizes ranging from 100 to 3000 nodes. Simulation results show low precision and recall for all of the above methods for large networks with a small number of expression profiles. We improved the inference significantly by refinement of the top weighted edges in the pre-inferred partial correlation networks using RLowPC. We found improved performance by partitioning large networks into smaller co-expressed modules when assessing the method performance within these modules. Conclusions The evaluation results show that current methods suffer from low precision and recall for large co-expression networks where only a small number of profiles are available. The proposed RLowPC method effectively reduces the indirect edges predicted as regulatory relationships and increases the precision of top ranked predictions. Partitioning large networks into smaller highly co-expressed modules also helps to improve the performance of network inference methods. The RLowPC R package for network construction, refinement and evaluation is available at GitHub: https://github.com/wyguo/RLowPC

Likely Role of APOBEC3G-Mediated G-to-A Mutations in HIV-1 Evolution and Drug Resistance

The role of APOBEC3 (A3) protein family members in inhibiting retrovirus infection and mobile element retrotransposition is well established. However, the evolutionary effects these restriction factors may have had on active retroviruses such as HIV-1 are less well understood. An HIV-1 variant that has been highly G-to-A mutated is unlikely to be transmitted due to accumulation of deleterious mutations. However, G-to-A mutated hA3G target sequences within which the mutations are the least deleterious are more likely to survive selection pressure. Thus, among hA3G targets in HIV-1, the ratio of nonsynonymous to synonymous changes will increase with virus generations, leaving a footprint of past activity. To study such footprints in HIV-1 evolution, we developed an in silico model based on calculated hA3G target probabilities derived from G-to-A mutation sequence contexts in the literature. We simulated G-to-A changes iteratively in independent sequential HIV-1 infections until a stop codon was introduced into any gene. In addition to our simulation results, we observed higher ratios of nonsynonymous to synonymous mutation at hA3G targets in extant HIV-1 genomes than in their putative ancestral genomes, compared to random controls, implying that moderate levels of A3G-mediated G-to-A mutation have been a factor in HIV-1 evolution. Results from in vitro passaging experiments of HIV-1 modified to be highly susceptible to hA3G mutagenesis verified our simulation accuracy. We also used our simulation to examine the possible role of A3G-induced mutations in the origin of drug resistance. We found that hA3G activity could have been responsible for only a small increase in mutations at known drug resistance sites and propose that concerns for increased resistance to other antiviral drugs should not prevent Vif from being considered a suitable target for development of new drugs