Evidence and modeling of turbulence bifurcation in L-mode confinement transitions on Alcator C-Mod

© 2020 Author(s). Analysis and modeling of rotation reversal hysteresis experiments show that a single turbulent bifurcation is responsible for the Linear to Saturated Ohmic Confinement (LOC/SOC) transition and concomitant intrinsic rotation reversal on Alcator C-Mod. Plasmas on either side of the reversal exhibit different toroidal rotation profiles and therefore different turbulence characteristics despite the profiles of density and temperature, which are indistinguishable within measurement uncertainty. Elements of this bifurcation are also shown to persist for auxiliary heated L-modes. The deactivation of subdominant (in the linear growth rate and contribution to heat transport) ion temperature gradient and trapped electron mode instabilities is identified as the only possible change in turbulence within a reduced quasilinear transport model across the reversal, which is consistent with the measured profiles and inferred heat and particle fluxes. Experimental constraints on a possible change from strong to weak turbulence, outside the description of the quasilinear model, are also discussed. These results indicate an explanation for the LOC/SOC transition that provides a mechanism for the hysteresis through the dynamics of subdominant modes and changes in their relative populations and does not involve a change in the most linearly unstable ion-scale drift-wave instability

Semantic aware Bayesian network model for actionable knowledge discovery in linked data

The majority of the conventional mining algorithms treat the mining process as an isolated data-driven procedure and overlook the semantic of the targeted data. As a result, the generated patterns are abundant and end users cannot act upon them seamlessly. Furthermore, interdisciplinary knowledge can not be obtained from domain-specific silo of data. The emergence of Linked Data (LD) as a new model for knowledge representation, which intertwines data with its semantics, has introduced new opportunities for data miners. Accordingly, this paper proposes an ontology-based Semantic-Aware Bayesian network (BN) model. In contrast to the existing mining algorithms, the proposed model does into transform the original format of the LD set. Therefore, it not only accommodates the semantic aspects in LD, but also caters to the need of connecting different data-sets from different domains. We evaluate the proposed model on a Bone Dysplasia dataset, Experimental results show promising performance

On Feedback Vertex Set: New Measure and New Structures

We present a new parameterized algorithm for the {feedback vertex set} problem ({\sc fvs}) on undirected graphs. We approach the problem by considering a variation of it, the {disjoint feedback vertex set} problem ({\sc disjoint-fvs}), which finds a feedback vertex set of size $k$ that has no overlap with a given feedback vertex set $F$ of the graph $G$. We develop an improved kernelization algorithm for {\sc disjoint-fvs} and show that {\sc disjoint-fvs} can be solved in polynomial time when all vertices in $G \setminus F$ have degrees upper bounded by three. We then propose a new branch-and-search process on {\sc disjoint-fvs}, and introduce a new branch-and-search measure. The process effectively reduces a given graph to a graph on which {\sc disjoint-fvs} becomes polynomial-time solvable, and the new measure more accurately evaluates the efficiency of the process. These algorithmic and combinatorial studies enable us to develop an $O^*(3.83^k)$-time parameterized algorithm for the general {\sc fvs} problem, improving all previous algorithms for the problem.Comment: Final version, to appear in Algorithmic

Near-Infrared Super Resolution Imaging with Metallic Nanoshell Particle Chain Array

We propose a near-infrared super resolution imaging system without a lens or a mirror but with an array of metallic nanoshell particle chain. The imaging array can plasmonically transfer the near-field components of dipole sources in the incoherent and coherent manners and the super resolution images can be reconstructed in the output plane. By tunning the parameters of the metallic nanoshell particle, the plasmon resonance band of the isolate nanoshell particle red-shifts to the near-infrared region. The near-infrared super resolution images are obtained subsequently. We calculate the field intensity distribution at the different planes of imaging process using the finite element method and find that the array has super resolution imaging capability at near-infrared wavelengths. We also show that the image formation highly depends on the coherence of the dipole sources and the image-array distance.Comment: 15 pages, 6 figure

Disentangling astroglial physiology with a realistic cell model in silico

Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K+ and generate Ca2+ signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which we constrain by empirical tests and integrate into the NEURON computational biophysical environment. This approach is implemented as a flexible astrocyte-model builder ASTRO. As a proof-of-concept, we explore an in silico astrocyte to evaluate basic cell physiology features inaccessible experimentally. Our simulations suggest that currents generated by glutamate transporters or K+ channels have negligible distant effects on membrane voltage and that individual astrocytes can successfully handle extracellular K+ hotspots. We show how intracellular Ca2+ buffers affect Ca2+ waves and why the classical Ca2+ sparks-and-puffs mechanism is theoretically compatible with common readouts of astroglial Ca2+ imaging

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and the Netherlands using respondent-driven sampling

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand

The Maximal U(1)LU(1)_L Inverse Seesaw from d=5d=5 Operator and Oscillating Asymmetric Sneutrino Dark Matter

The maximal $U(1)_L$ supersymmetric inverse seesaw mechanism (M$L$SIS) provides a natural way to relate asymmetric dark matter (ADM) with neutrino physics. In this paper we point out that, M$L$SIS is a natural outcome if one dynamically realizes the inverse seesaw mechanism in the next-to minimal supersymmetric standard model (NMSSM) via the dimension-five operator $(N)^2S^2/M_*$, with $S$ the NMSSM singlet developing TeV scale VEV; it slightly violates lepton number due to the suppression by the fundamental scale $M_*$, thus preserving $U(1)_L$ maximally. The resulting sneutrino is a distinguishable ADM candidate, oscillating and favored to have weak scale mass. A fairly large annihilating cross section of such a heavy ADM is available due to the presence of singlet.Comment: journal versio

Rare B Decays with a HyperCP Particle of Spin One

In light of recent experimental information from the CLEO, BaBar, KTeV, and Belle collaborations, we investigate some consequences of the possibility that a light spin-one particle is responsible for the three Sigma^+ -> p mu^+ mu^- events observed by the HyperCP experiment. In particular, allowing the new particle to have both vector and axial-vector couplings to ordinary fermions, we systematically study its contributions to various processes involving b-flavored mesons, including B-Bbar mixing as well as leptonic, inclusive, and exclusive B decays. Using the latest experimental data, we extract bounds on its couplings and subsequently estimate upper limits for the branching ratios of a number of B decays with the new particle. This can serve to guide experimental searches for the particle in order to help confirm or refute its existence.Comment: 17 pages, 3 figures; discussion on spin-0 case modified, few errors corrected, main conclusions unchange

Combination of electroweak and QCD corrections to single W production at the Fermilab Tevatron and the CERN LHC

Precision studies of the production of a high-transverse momentum lepton in association with missing energy at hadron colliders require that electroweak and QCD higher-order contributions are simultaneously taken into account in theoretical predictions and data analysis. Here we present a detailed phenomenological study of the impact of electroweak and strong contributions, as well as of their combination, to all the observables relevant for the various facets of the p\smartpap \to {\rm lepton} + X physics programme at hadron colliders, including luminosity monitoring and Parton Distribution Functions constraint, $W$ precision physics and search for new physics signals. We provide a theoretical recipe to carefully combine electroweak and strong corrections, that are mandatory in view of the challenging experimental accuracy already reached at the Fermilab Tevatron and aimed at the CERN LHC, and discuss the uncertainty inherent the combination. We conclude that the theoretical accuracy of our calculation can be conservatively estimated to be about 2% for standard event selections at the Tevatron and the LHC, and about 5% in the very high $W$ transverse mass/lepton transverse momentum tails. We also provide arguments for a more aggressive error estimate (about 1% and 3%, respectively) and conclude that in order to attain a one per cent accuracy: 1) exact mixed ${\cal O}(\alpha \alpha_s)$ corrections should be computed in addition to the already available NNLO QCD contributions and two-loop electroweak Sudakov logarithms; 2) QCD and electroweak corrections should be coherently included into a single event generator.Comment: One reference added. Final version to appear in JHE

Tetraspanin (TSP-17) Protects Dopaminergic Neurons against 6-OHDA-Induced Neurodegeneration in <i>C. elegans</i>

Parkinson's disease (PD), the second most prevalent neurodegenerative disease after Alzheimer's disease, is linked to the gradual loss of dopaminergic neurons in the substantia nigra. Disease loci causing hereditary forms of PD are known, but most cases are attributable to a combination of genetic and environmental risk factors. Increased incidence of PD is associated with rural living and pesticide exposure, and dopaminergic neurodegeneration can be triggered by neurotoxins such as 6-hydroxydopamine (6-OHDA). In C. elegans, this drug is taken up by the presynaptic dopamine reuptake transporter (DAT-1) and causes selective death of the eight dopaminergic neurons of the adult hermaphrodite. Using a forward genetic approach to find genes that protect against 6-OHDA-mediated neurodegeneration, we identified tsp-17, which encodes a member of the tetraspanin family of membrane proteins. We show that TSP-17 is expressed in dopaminergic neurons and provide genetic, pharmacological and biochemical evidence that it inhibits DAT-1, thus leading to increased 6-OHDA uptake in tsp-17 loss-of-function mutants. TSP-17 also protects against toxicity conferred by excessive intracellular dopamine. We provide genetic and biochemical evidence that TSP-17 acts partly via the DOP-2 dopamine receptor to negatively regulate DAT-1. tsp-17 mutants also have subtle behavioral phenotypes, some of which are conferred by aberrant dopamine signaling. Incubating mutant worms in liquid medium leads to swimming-induced paralysis. In the L1 larval stage, this phenotype is linked to lethality and cannot be rescued by a dop-3 null mutant. In contrast, mild paralysis occurring in the L4 larval stage is suppressed by dop-3, suggesting defects in dopaminergic signaling. In summary, we show that TSP-17 protects against neurodegeneration and has a role in modulating behaviors linked to dopamine signaling