Coherent coupling between surface plasmons and excitons in semiconductor nanocrystals

We present an experimental demonstration of strong coupling between a surface plasmon propagating on a planar silver substrate, and the lowest excited state of CdSe nanocrystals. Variable-angle spectroscopic ellipsometry measurements demonstrated the formation of plasmon-exciton mixed states, characterized by a Rabi splitting of $\sim$ 82 meV at room temperature. Such a coherent interaction has the potential for the development of plasmonic non-linear devices, and furthermore, this system is akin to those studied in cavity quantum electrodynamics, thus offering the possibility to study the regime of strong light-matter coupling in semiconductor nanocrystals at easily accessible experimental conditions.Comment: 12 pages, 4 figure

On the ill/well-posedness and nonlinear instability of the magneto-geostrophic equations

We consider an active scalar equation that is motivated by a model for magneto-geostrophic dynamics and the geodynamo. We prove that the non-diffusive equation is ill-posed in the sense of Hadamard in Sobolev spaces. In contrast, the critically diffusive equation is well-posed. In this case we give an example of a steady state that is nonlinearly unstable, and hence produces a dynamo effect in the sense of an exponentially growing magnetic field.Comment: We have modified the definition of Lipschitz well-posedness, in order to allow for a possible loss in regularity of the solution ma

Optothermotronic effect as an ultrasensitive thermal sensing technology for solid-state electronics

The thermal excitation, regulation, and detection of charge carriers in solid-state electronics have attracted great attention toward high-performance sensing applications but still face major challenges. Manipulating thermal excitation and transport of charge carriers in nanoheterostructures, we report a giant temperature sensing effect in semiconductor nanofilms via optoelectronic coupling, termed optothermotronics. A gradient of charge carriers in the nanofilms under nonuniform light illumination is coupled with an electric tuning current to enhance the performance of the thermal sensing effect. As a proof of concept, we used silicon carbide (SiC) nanofilms that form nanoheterostructures on silicon (Si). The sensing performance based on the thermal excitation of charge carriers in SiC is enhanced by at least 100 times through photon excitation, with a giant temperature coefficient of resistance (TCR) of up to −50%/K. Our findings could be used to substantially enhance the thermal sensing performance of solid-state electronics beyond the present sensing technologies

Limit on the Temporal Variation of the Fine-Structure Constant Using Atomic Dysprosium

Over a period of eight months, we have monitored transition frequencies between nearly degenerate, opposite-parity levels in two isotopes of atomic dysprosium (Dy). These transition frequencies are highly sensitive to temporal variation of the fine-structure constant ($\alpha$) due to relativistic corrections of large and opposite sign for the opposite-parity levels. In this unique system, in contrast to atomic-clock comparisons, the difference of the electronic energies of the opposite-parity levels can be monitored directly utilizing a radio-frequency (rf) electric-dipole transition between them. Our measurements show that the frequency variation of the 3.1-MHz transition in $^{163}$Dy and the 235-MHz transition in $^{162}$Dy are 9.0$\pm$6.7 Hz/yr and -0.6$\pm$6.5 Hz/yr, respectively. These results provide a value for the rate of fractional variation of $\alpha$ of $(-2.7\pm2.6)\times 10^{-15}$ yr$^{-1}$ (1 $\sigma$) without any assumptions on the constancy of other fundamental constants, indicating absence of significant variation at the present level of sensitivity.Comment: 4 pages, 2 figure

Elasticity Theory and Shape Transitions of Viral Shells

Recently, continuum elasticity theory has been applied to explain the shape transition of icosahedral viral capsids - single-protein-thick crystalline shells - from spherical to buckled/faceted as their radius increases through a critical value determined by the competition between stretching and bending energies of a closed 2D elastic network. In the present work we generalize this approach to capsids with non-icosahedral symmetries, e.g., spherocylindrical and conical shells. One key new physical ingredient is the role played by nonzero spontaneous curvature. Another is associated with the special way in which the energy of the twelve topologically-required five-fold sites depends on the background local curvature of the shell in which they are embedded. Systematic evaluation of these contributions leads to a shape phase diagram in which transitions are observed from icosahedral to spherocylindrical capsids as a function of the ratio of stretching to bending energies and of the spontaneous curvature of the 2D protein network. We find that the transition from icosahedral to spherocylindrical symmetry is continuous or weakly first-order near the onset of buckling, leading to extensive shape degeneracy. These results are discussed in the context of experimentally observed variations in the shapes of a variety of viral capsids.Comment: 53 pages, 17 figure

Network structure indexes to forecast epidemic spreading in real-world complex networks

Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks

Considering weights in real social networks: A review

Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences

A randomized controlled trial of a pharmacist-led intervention to enhance knowledge of Vietnamese patients with type 2 diabetes mellitus

OBJECTIVES: We aimed to assess whether a pharmacist-led intervention enhances knowledge, medication adherence and glycemic control in patients with type 2 diabetes mellitus (T2DM). METHODS: We conducted a single-blinded randomized controlled trial in Vietnam. Individuals with T2DM were recruited from a general hospital and randomly allocated to intervention and routine care. The intervention group received routine care plus counselling intervention by a pharmacist, including providing drug information and answering individual patients' queries relating to T2DM and medications, which had not been done in routine care. We assessed the outcomes: knowledge score as measured by the Diabetes Knowledge Questionnaire, self-reported adherence and fasting blood glucose (FBG) at the 1-month follow-up. KEY FINDINGS: A total of 165 patients (83 intervention, 82 control) completed the study; their mean age was 63.33 years, and 49.1% were males. The baseline characteristics of the patients were similar between the groups. At 1-month follow-up, the pharmacist's intervention resulted in an improvement in all three outcomes: knowledge score [B = 5.527; 95% confidence intervals (CI): 3.982 to 7.072; P < 0.001], adherence [odds ratio (OR) = 9.813; 95% CI: 2.456 to 39.205; P = 0.001] and attainment of target FBG (OR = 1.979; 95% CI: 1.029 to 3.806; P = 0.041). CONCLUSIONS: The pharmacist-led intervention enhanced disease knowledge, medication adherence and glycemic control in patients with T2DM. This study provides evidence of the benefits of pharmacist counselling in addition to routine care for T2DM outpatients in a Vietnam population