Decay and coherence of two-photon excited yellow ortho-excitons in Cu2O

Photoluminescence excitation spectroscopy has revealed a novel, highly efficient two-photon excitation method to produce a cold, uniformly distributed high density excitonic gas in bulk cuprous oxide. A study of the time evolution of the density, temperature and chemical potential of the exciton gas shows that the so called quantum saturation effect that prevents Bose-Einstein condensation of the ortho-exciton gas originates from an unfavorable ratio between the cooling and recombination rates. Oscillations observed in the temporal decay of the ortho-excitonic luminescence intensity are discussed in terms of polaritonic beating. We present the semiclassical description of polaritonic oscillations in linear and non-linear optical processes.Comment: 14 pages, 12 figure

KINEROS2 application for land use/cover change impact analysis at the Hulu Langat Basin, Malaysia

The impacts of land use/cover changes (LUCC) on a developed basin in Malaysia were evaluated. Three storm events in different intensities and durations were required for KINEROS2 (K2) calibration and LUCC impact analysis. K2 validation was performed using three other rainfall events. Calibration results showed excellent and very good fittings for runoff and sediment simulations based on the aggregated measure. Validation results demonstrated that the K2 is reliable for runoff modelling, while K2 application for sediment simulation was only valid for the period 1984-1997. LUCC impacts analysis revealed that direct runoff and sediment discharge increased with the progress of urban development and unmanaged agricultural activities. These observations were supported by the NDVI, landscape and hydrological trend analyses

Mechanical signatures of microbial biofilms in micropillar-embedded growth chambers

Biofilms are surface-attached communities of microorganisms embedded in an extracellular matrix and are essential for the cycling of organic matter in natural and engineered environments. They are also the leading cause of many infections, for example, those associated with chronic wounds and implanted medical devices. The extracellular matrix is a key biofilm component that determines its architecture and defines its physical properties. Herein, we used growth chambers embedded with micropillars to study the net mechanical forces (differential pressure) exerted during biofilm formation in situ. Pressure from the biofilm is transferred to the micropillars via the extracellular matrix, and reduction of major matrix components decreases the magnitude of micropillar deflections. The spatial arrangement of micropillar deflections caused by pressure differences in the different biofilm strains may potentially be used as mechanical signatures for biofilm characterization. Hence, we submit that micropillar-embedded growth chambers provide insights into the mechanical properties and dynamics of the biofilm and its matrix.Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology (SMART)

From Heisenberg matrix mechanics to EBK quantization: theory and first applications

Despite the seminal connection between classical multiply-periodic motion and Heisenberg matrix mechanics and the massive amount of work done on the associated problem of semiclassical (EBK) quantization of bound states, we show that there are, nevertheless, a number of previously unexploited aspects of this relationship that bear on the quantum-classical correspondence. In particular, we emphasize a quantum variational principle that implies the classical variational principle for invariant tori. We also expose the more indirect connection between commutation relations and quantization of action variables. With the help of several standard models with one or two degrees of freedom, we then illustrate how the methods of Heisenberg matrix mechanics described in this paper may be used to obtain quantum solutions with a modest increase in effort compared to semiclassical calculations. We also describe and apply a method for obtaining leading quantum corrections to EBK results. Finally, we suggest several new or modified applications of EBK quantization.Comment: 37 pages including 3 poscript figures, submitted to Phys. Rev.

GAUBERT, Joël, La Science politique d’Ernst Cassirer. Pour une refondation symbolique de la raison pratique contre le mythe politique contemporain

In recent years, with the widespread usage of Web 2.0 techniques, crowdsourcing plays an important role in offering human intelligence in various service websites, such as Yahoo! Answer and Quora. With the increasing amount of crowd-oriented service data, an important task is to analyze latest hot topics and track topic evolution over time. However, the existing techniques in text mining cannot effectively work due to the unique structure of crowd-oriented service data, task-response pairs, which consists of the task and its corresponding responses. In particular, existing approaches become ineffective with the ever-increasing crowd-oriented service data that accumulate along the time. In this paper, we first study the problem of discovering topics over crowd-oriented service data. Then we propose a new probabilistic topic model, the Topic Crowd Service Model (TCS model), to effectively discover latent topics from massive crowd-oriented service data. In particular, in order to train TCS efficiently, we design a novel parameter inference algorithm, the Bucket Parameter Estimation (BPE), which utilizes belief propagation and a new sketching technique, called Pairwise Sketch (pSketch). Finally, we conduct extensive experiments to verify the effectiveness and efficiency of the TCS model and the BPE algorithm. © 2014 ACM

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future