Nanoscale plasmonic resonators with high Purcell factor: Spontaneous and stimulated emission

Plasmonic nanoparticles with silver cores and silica shells containing Eu fluorophores near the surface have been produced by wet chemistry method and their spontaneous emission properties characterized. Fluorescence amplification and decreased lifetime is interpreted within the Purcell framework which highlights the role of surface plasmon polariton modes of the nanoparticle. These behave as energy-storing resonators, with values of the Q factor between 50 and 170 at the fluorophore wavelength of 615 nm, and very small mode volumes, in the order of 104 nm3, producing high Purcell factors of over 4000. Comparison of experiment with theoretical calculations by using the Mie theory shows that the values of cavity Q factors are moderated by the nonradiative rate of fluorophore molecules close to metal. The criteria for laser action in such composite nanoparticles are also presented, including lasing frequencies and threshold gain. © 2011 SPIE

Community Aliveness: Discovering Interaction Decay Patterns in Online Social Communities

Online Social Communities (OSCs) provide a medium for connecting people, sharing news, eliciting information, and finding jobs, among others. The dynamics of the interaction among the members of OSCs is not always growth dynamics. Instead, a $\textit{decay}$ or $\textit{inactivity}$ dynamics often happens, which makes an OSC obsolete. Understanding the behavior and the characteristics of the members of an inactive community help to sustain the growth dynamics of these communities and, possibly, prevents them from being out of service. In this work, we provide two prediction models for predicting the interaction decay of community members, namely: a Simple Threshold Model (STM) and a supervised machine learning classification framework. We conducted evaluation experiments for our prediction models supported by a $\textit{ground truth}$ of decayed communities extracted from the StackExchange platform. The results of the experiments revealed that it is possible, with satisfactory prediction performance in terms of the F1-score and the accuracy, to predict the decay of the activity of the members of these communities using network-based attributes and network-exogenous attributes of the members. The upper bound of the prediction performance of the methods we used is $0.91$ and $0.83$ for the F1-score and the accuracy, respectively. These results indicate that network-based attributes are correlated with the activity of the members and that we can find decay patterns in terms of these attributes. The results also showed that the structure of the decayed communities can be used to support the alive communities by discovering inactive members.Comment: pre-print for the 4th European Network Intelligence Conference - 11-12 September 2017 Duisburg, German

The impact of chromosomal translocation locus and fusion oncogene coding sequence in synovial sarcomagenesis.

Synovial sarcomas are aggressive soft-tissue malignancies that express chromosomal translocation-generated fusion genes, SS18-SSX1 or SS18-SSX2 in most cases. Here, we report a mouse sarcoma model expressing SS18-SSX1, complementing our prior model expressing SS18-SSX2. Exome sequencing identified no recurrent secondary mutations in tumors of either genotype. Most of the few mutations identified in single tumors were present in genes that were minimally or not expressed in any of the tumors. Chromosome 6, either entirely or around the fusion gene expression locus, demonstrated a copy number gain in a majority of tumors of both genotypes. Thus, by fusion oncogene coding sequence alone, SS18-SSX1 and SS18-SSX2 can each drive comparable synovial sarcomagenesis, independent from other genetic drivers. SS18-SSX1 and SS18-SSX2 tumor transcriptomes demonstrated very few consistent differences overall. In direct tumorigenesis comparisons, SS18-SSX2 was slightly more sarcomagenic than SS18-SSX1, but equivalent in its generation of biphasic histologic features. Meta-analysis of human synovial sarcoma patient series identified two tumor-gentoype-phenotype correlations that were not modeled by the mice, namely a scarcity of male hosts and biphasic histologic features among SS18-SSX2 tumors. Re-analysis of human SS18-SSX1 and SS18-SSX2 tumor transcriptomes demonstrated very few consistent differences, but highlighted increased native SSX2 expression in SS18-SSX1 tumors. This suggests that the translocated locus may drive genotype-phenotype differences more than the coding sequence of the fusion gene created. Two possible roles for native SSX2 in synovial sarcomagenesis are explored. Thus, even specific partial failures of mouse genetic modeling can be instructive to human tumor biology

Integrate and Fire Neural Networks, Piecewise Contractive Maps and Limit Cycles

We study the global dynamics of integrate and fire neural networks composed of an arbitrary number of identical neurons interacting by inhibition and excitation. We prove that if the interactions are strong enough, then the support of the stable asymptotic dynamics consists of limit cycles. We also find sufficient conditions for the synchronization of networks containing excitatory neurons. The proofs are based on the analysis of the equivalent dynamics of a piecewise continuous Poincar\'e map associated to the system. We show that for strong interactions the Poincar\'e map is piecewise contractive. Using this contraction property, we prove that there exist a countable number of limit cycles attracting all the orbits dropping into the stable subset of the phase space. This result applies not only to the Poincar\'e map under study, but also to a wide class of general n-dimensional piecewise contractive maps.Comment: 46 pages. In this version we added many comments suggested by the referees all along the paper, we changed the introduction and the section containing the conclusions. The final version will appear in Journal of Mathematical Biology of SPRINGER and will be available at http://www.springerlink.com/content/0303-681

Learning Moore Machines from Input-Output Traces

The problem of learning automata from example traces (but no equivalence or membership queries) is fundamental in automata learning theory and practice. In this paper we study this problem for finite state machines with inputs and outputs, and in particular for Moore machines. We develop three algorithms for solving this problem: (1) the PTAP algorithm, which transforms a set of input-output traces into an incomplete Moore machine and then completes the machine with self-loops; (2) the PRPNI algorithm, which uses the well-known RPNI algorithm for automata learning to learn a product of automata encoding a Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore machine using PTAP extended with state merging. We prove that MooreMI has the fundamental identification in the limit property. We also compare the algorithms experimentally in terms of the size of the learned machine and several notions of accuracy, introduced in this paper. Finally, we compare with OSTIA, an algorithm that learns a more general class of transducers, and find that OSTIA generally does not learn a Moore machine, even when fed with a characteristic sample

Practical implementation, characterization and applications of a multi-colour time-gated luminescence microscope

Time-gated luminescence microscopy using long-lifetime molecular probes can effectively eliminate autofluorescence to enable high contrast imaging. Here we investigate a new strategy of time-gated imaging for simultaneous visualisation of multiple species of microorganisms stained with long-lived complexes under low-background conditions. This is realized by imaging two pathogenic organisms (Giardia lamblia stained with a red europium probe and Cryptosporidium parvum with a green terbium probe) at UV wavelengths (320-400 nm) through synchronization of a flash lamp with high repetition rate (1 kHz) to a robust time-gating detection unit. This approach provides four times enhancement in signal-to-background ratio over non-time-gated imaging, while the average signal intensity also increases six-fold compared with that under UV LED excitation. The high sensitivity is further confirmed by imaging the single europium-doped Y2O2S nanocrystals (150 nm). We report technical details regarding the time-gating detection unit and demonstrate its compatibility with commercial epi-fluorescence microscopes, providing a valuable and convenient addition to standard laboratory equipment

Coordination of opposing sex-specific and core muscle groups regulates male tail posture during Caenorhabditis elegans male mating behavior

Background To survive and reproduce, animals must be able to modify their motor behavior in response to changes in the environment. We studied a complex behavior of Caenorhabditis elegans, male mating behavior, which provided a model for understanding motor behaviors at the genetic, molecular as well as circuit level. C. elegans male mating behavior consists of a series of six sub-steps: response to contact, backing, turning, vulva location, spicule insertion, and sperm transfer. The male tail contains most of the sensory structures required for mating, in addition to the copulatory structures, and thus to carry out the steps of mating behavior, the male must keep his tail in contact with the hermaphrodite. However, because the hermaphrodite does not play an active role in mating and continues moving, the male must modify his tail posture to maintain contact. We provide a better understanding of the molecular and neuro-muscular pathways that regulate male tail posture during mating. Results Genetic and laser ablation analysis, in conjunction with behavioral assays were used to determine neurotransmitters, receptors, neurons and muscles required for the regulation of male tail posture. We showed that proper male tail posture is maintained by the coordinated activity of opposing muscle groups that curl the tail ventrally and dorsally. Specifically, acetylcholine regulates both ventral and dorsal curling of the male tail, partially through anthelmintic levamisole-sensitive, nicotinic receptor subunits. Male-specific muscles are required for acetylcholine-driven ventral curling of the male tail but dorsal curling requires the dorsal body wall muscles shared by males and hermaphrodites. Gamma-aminobutyric acid activity is required for both dorsal and ventral acetylcholine-induced curling of the male tail and an inhibitory gamma-aminobutyric acid receptor, UNC-49, prevents over-curling of the male tail during mating, suggesting that cross-inhibition of muscle groups helps maintain proper tail posture. Conclusion Our results demonstrated that coordination of opposing sex-specific and core muscle groups, through the activity of multiple neurotransmitters, is required for regulation of male tail posture during mating. We have provided a simple model for regulation of male tail posture that provides a foundation for studies of how genes, molecular pathways, and neural circuits contribute to sensory regulation of this motor behavior