Nonequilibrium dynamics of photoexcited electrons in graphene: Collinear scattering, Auger processes, and the impact of screening

We present a combined analytical and numerical study of the early stages (sub-100-fs) of the nonequilibrium dynamics of photoexcited electrons in graphene. We employ the semiclassical Boltzmann equation with a collision integral that includes contributions from electron-electron (e-e) and electron-optical phonon interactions. Taking advantage of circular symmetry and employing the massless Dirac fermion (MDF) Hamiltonian, we are able to perform an essentially analytical study of the e-e contribution to the collision integral. This allows us to take particular care of subtle collinear scattering processes - processes in which incoming and outgoing momenta of the scattering particles lie on the same line - including carrier multiplication (CM) and Auger recombination (AR). These processes have a vanishing phase space for two-dimensional MDF bare bands. However, we argue that electron-lifetime effects, seen in experiments based on angle-resolved photoemission spectroscopy, provide a natural pathway to regularize this pathology, yielding a finite contribution due to CM and AR to the Coulomb collision integral. Finally, we discuss in detail the role of physics beyond the Fermi golden rule by including screening in the matrix element of the Coulomb interaction at the level of the random phase approximation (RPA), focusing in particular on the consequences of various approximations including static RPA screening, which maximizes the impact of CM and AR processes, and dynamical RPA screening, which completely suppresses them. © 2013 American Physical Society.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

Numerical simulations supporting the process design of ring rolling processes

In conventional Finite Element Analysis (FEA) of radial-axial ring rolling (RAR) the motions of all tools are usually defined prior to simulation in the preprocessing step. However, the real process holds up to 8 degrees of freedom (DOF) that are controlled by industrial control systems according to actual sensor values and preselected control strategies. Since the histories of the motions are unknown before the experiment and are dependent on sensor data, the conventional FEA cannot represent the process before experiment. In order to enable the usage of FEA in the process design stage, this approach integrates the industrially applied control algorithms of the real process including all relevant sensors and actuators into the FE model of ring rolling. Additionally, the process design of a novel process 'the axial profiling', in which a profiled roll is used for rolling axially profiled rings, is supported by FEA. Using this approach suitable control strategies can be tested in virtual environment before processing. © 2013 AIP Publishing LLC.

Communities of gastrointestinal helminths of fish in historically connected habitats: habitat fragmentation effect in a carnivorous catfish Pelteobagrus fulvidraco from seven lakes in flood plain of the Yangtze River, China

Background: Habitat fragmentation may result in the reduction of diversity of parasite communities by affecting population size and dispersal pattern of species. In the flood plain of the Yangtze River in China, many lakes, which were once connected with the river, have become isolated since the 1950s from the river by the construction of dams and sluices, with many larger lakes subdivided into smaller ones by road embankments. These artificial barriers have inevitably obstructed the migration of fish between the river and lakes and also among lakes. In this study, the gastrointestinal helminth communities were investigated in a carnivorous fish, the yellowhead catfish Pelteobagrus fulvidraco, from two connected and five isolated lakes in the flood plain in order to detect the effect of lake fragmentation on the parasite communities. Results: A total of 11 species of helminths were recorded in the stomach and intestine of P. fulvidraco from seven lakes, including two lakes connected with the Yangtze River, i.e. Poyang and Dongting lakes, and five isolated lakes, i.e. Honghu, Liangzi, Tangxun, Niushan and Baoan lakes. Mean helminth individuals and diversity of helminth communities in Honghu and Dongting lakes was lower than in the other five lakes. The nematode Procamallanus fulvidraconis was the dominant species of communities in all the seven lakes. No significant difference in the Shannon-Wiener index was detected between connected lakes (0.48) and isolated lakes (0.50). The similarity of helminth communities between Niushan and Baoan lakes was the highest (0.6708), and the lowest was between Tangxun and Dongting lakes (0.1807). The similarity was low between Dongting and the other lakes, and the similarity decreased with the geographic distance among these lakes. The helminth community in one connected lake, Poyang Lake was clustered with isolated lakes, but the community in Dongting Lake was separated in the tree. Conclusion: The similarity in the helminth communities of this fish in the flood-plain lakes may be attributed to the historical connection of these habitats and to the completion of the life-cycles of this fish as well as the helminth species within the investigated habitats. The diversity and the digenean majority in the helminth communities can be related to the diet of this fish, and to the lacustrine and macrophytic characters of the habitats. The lake isolation from the river had little detectable effect on the helminth communities of the catfish in flood-plain lakes of the Yangtze River. The low similarities in helminth communities between the Dongting Lake and others may just be a reflection of its unique water environment and anthropogenic alterations or fragmentation in this lake.

Student-t processes as alternatives to Gaussian processes

We investigate the Student-t process as an alternative to the Gaussian process as a non-parametric prior over functions. We derive closed form expressions for the marginal likelihood and predictive distribution of a Student-t process, by integrating away an inverse Wishart process prior over the co-variance kernel of a Gaussian process model. We show surprising equivalences between different hierarchical Gaussian process models leading to Student-t processes, and derive a new sampling scheme for the inverse Wishart process, which helps elucidate these equivalences. Overall, we show that a Student-t process can retain the attractive properties of a Gaussian process - a nonparamet-ric representation, analytic marginal and predictive distributions, and easy model selection through covariance kernels - but has enhanced flexibility, and predictive covariances that, unlike a Gaussian process, explicitly depend on the values of training observations. We verify empirically that a Student-t process is especially useful in situations where there are changes in covariance structure, or in applications such as Bayesian optimization, where accurate predictive covariances are critical for good performance. These advantages come at no additional computational cost over Gaussian processes.

Genetic variation of fish parasite populations in historically connected habitats: undetected habitat fragmentation effect on populations of the nematode Procamallanus fulvidraconis in the catfish Pelteobagrus fulvidraco

Habitat fragmentation may have some significant effects on population genetic structure because geographic distance and physical barriers may impede gene flow between populations. In this study, we investigated whether recent habitat fragmentation affected genetic structure and diversity of populations of the nematode Procamallanus fulvidraconis in the yellowhead catfish, Pelteobagrus fin't4draco. The nematode was collected from 12 localities in 7 floodplain lakes of the Yangtze River. Using I I intersirnple sequence repeat markers, analysis of molecular variance showed that genetic diversity occurred mainly within populations (70.26%). Expected heterozygosity (He) of P. fulvidraconis was barely different between connected (0.2105) and unconnected lakes (0.2083). Population subdivision (Fst) between connected lakes (0.2177) was higher than in unconnected lakes (0. 1676). However, the connected and unconnected lakes did not Cluster into 2 clades. A Mantel test revealed significant positive correlation between genetic and geographic distances (R = 0.5335, P < 0.01). These results suggest that habitat fragmentation did not cause genetic differentiation among populations or a reduction of diversity in isolated populations of P. fulvidraconis. At least 2 factors may increase the dispersal range of the nematode, i.e., flash flooding in summer and other species of fish that may serve as the definitive hosts. Moreover, lake fragmentation is probably a recent process; population size of the nematode in these lakes is large enough to maintain Population structure.

TRAIL in the mandarin fish Siniperca chuatsi: Gene and its apoptotic effect in HeLa cells

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is one of the TNF superfamily members, participating in many biological processes including cell proliferation and apoptotic death. In this study, a TRAIL gene was cloned from a perciform fish, the mandarin fish Siniperca chuatsi, a major cultured fish in China's aquaculture, and is named as SCTRAIL for S. chuatsi TRAIL. The full-length cDNA of SCTRAIL is 1359 bp, encoding a 283-amino-acid protein. This deduced protein contains the CYS231, a 23-mer fragment of transmembrane region, a glycosylation site and a TNF family signature, all of which are conserved among TRAIL members. SCTRAIL gene consists of six exons, with five intervening introns, spaced over approximately 9 kb of genomic sequence. Southern blotting demonstrated that the SCTRAIL gene is present as a single copy in mandarin fish genome. A 620 bp promoter region obtained by genome walking contains a number of putative transcription factor binding sites, such as Oct-1, Sp-1, NF-1, RAP-1, C/EBPaLp, NF-kappa B and AP-1. The SCTRAIL is constitutively expressed in all the analyzed tissues, as revealed by RT-PCR, which is confirmed by Western blotting analysis using polyclonal antibody against bacteria-derived recombinant SCTRAIL protein. As an apoptosis-inducing ligand, the overexpression of SCTRAIL but not the mutant SCTRAIL-C203S in HeLa cells induced changes characteristic of apoptosis, including chromatin condensation, nucleus fragmentation, DNA ladder, and increase of sub-G0/G1 cells in FACS analysis. (c) 2007 Elsevier Ltd. All rights reserved.

Fault tolerant control using Gaussian processes and model predictive control

Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control. © 2013 IEEE.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

Characterizing the class of local metal sheet thickening processes

The need to create high-value products for specialist applications, and the search for efficient forming routes that obviate the need for some machining steps, is driving Interest In a novel class of forming processes aiming to create locally thickened features within sheet work- pieces. A number of novel forming processes have been proposed to meet this need, but it is as yet unclear which processes will be most effective in creating local thickening of various geometries, and many process configurations have yet to be tried. This paper aims to provide some basic principles for designing and characterising process behaviour. A simplified generic description of sheet thickening processes is provided, with two tools of variable operating on a sheet workpiece in plane strain, with different tool separations and motions parameterised. A comprehensive numerical study of the behaviour of this class of processes is conducted in Abaqus to predict the main characteristics of the material flow in each configuration. The results are used to classify the different basic behaviours that can be achieved by the sheet-bulk thickening processes and to give guidance on future process development, capability and applicability. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

Classification using log Gaussian Cox processes

McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing properties. Conditioned on the covariates, the distribution over labels is given by a type of conditional Markov random field. In the supervised case, computation of the predictive probability of a single test point scales linearly with the number of training points and the multiclass generalization is straightforward. We show new links between the supervised method and classical nonparametric methods. We give a detailed analysis of the pairwise graph representable Markov random field, which we use to extend the model to semi-supervised learning problems, and propose an inference method based on graph min-cuts. We give the first experimental analysis on supervised and semi-supervised datasets and show good empirical performance.

Direct observation of coherent spin transfer processes in an InGaAs/GaAs quantum well via two-color time-resolved Kerr rotation measurements

A two-color time-resolved Kerr rotation spectroscopy system was built, with a femtosecond Ti:sapphire laser and a photonic crystal fiber, to study coherent spin transfer processes in an InGaAs/GaAs quantum well sample. The femtosecond Ti:sapphire laser plays two roles: besides providing a pump beam with a tunable wavelength, it also excites the photonic crystal fiber to generate supercontinuum light ranging from 500 nm to 1600 nm, from which a probe beam with a desirable wavelength is selected with a suitable interference filter. With such a system, we studied spin transfer processes between two semiconductors of different gaps in an InGaAs/GaAs quantum well sample. We found that electron spins generated in the GaAs barrier were transferred coherently into the InGaAs quantum well. A model based on rate equations and Bloch-Torrey equations is used to describe the coherent spin transfer processes quantitatively. With this model, we obtain an effective electron spin accumulation time of 21 ps in the InGaAs quantum well.

Optical analysis of dislocation-related physical processes in GaN-based epilayers

In this paper, recent progresses in optical analysis of dislocation-related physical properties in GaN-based epilayers are surveyed with a brief review. The influence of dislocations on both near-band edge emission and yellow luminescence (YL) is examined either in a statistical way as a function of dislocation density or focused on individual dislocation lines with a high spatial resolution. Threading dislocations may introduce non-radiative recombination centers and enhance YL, but their effects are affected by the structural and chemical environment. The minority carrier diffusion length may be dependent on either dislocation density or impurity doping as confirmed by the result of photovoltaic spectra. The in situ optical monitoring of the strain evolution process is employed during GaN heteroepitaxy using an AIN interlayer. A typical transition of strain from compression to tension is observed and its correlation with the reduction and inclination of threading dislocation lines is revealed. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.