Frequency-based brain networks: From a multiplex framework to a full multilayer description

We explore how to study dynamical interactions between brain regions using functional multilayer networks whose layers represent the different frequency bands at which a brain operates. Specifically, we investigate the consequences of considering the brain as a multilayer network in which all brain regions can interact with each other at different frequency bands, instead of as a multiplex network, in which interactions between different frequency bands are only allowed within each brain region and not between them. We study the second smallest eigenvalue of the combinatorial supra-Laplacian matrix of the multilayer network in detail, and we thereby show that the heterogeneity of interlayer edges and, especially, the fraction of missing edges crucially modify the spectral properties of the multilayer network. We illustrate our results with both synthetic network models and real data sets obtained from resting state magnetoencephalography. Our work demonstrates an important issue in the construction of frequency-based multilayer brain networks.Comment: 13 pages, 8 figure

The impact of vaporized nanoemulsions on ultrasound-mediated ablation

BACKGROUND: The clinical feasibility of using high-intensity focused ultrasound (HIFU) for ablation of solid tumors is limited by the high acoustic pressures and long treatment times required. The presence of microbubbles during sonication can increase the absorption of acoustic energy and accelerate heating. However, formation of microbubbles within the tumor tissue remains a challenge. Phase-shift nanoemulsions (PSNE) have been developed as a means for producing microbubbles within tumors. PSNE are emulsions of submicron-sized, lipid-coated, and liquid perfluorocarbon droplets that can be vaporized into microbubbles using short (5 MPa) acoustic pulses. In this study, the impact of vaporized phase-shift nanoemulsions on the time and acoustic power required for HIFU-mediated thermal lesion formation was investigated in vitro. METHODS: PSNE containing dodecafluoropentane were produced with narrow size distributions and mean diameters below 200 nm using a combination of sonication and extrusion. PSNE was dispersed in albumin-containing polyacrylamide gel phantoms for experimental tests. Albumin denatures and becomes opaque at temperatures above 58°C, enabling visual detection of lesions formed from denatured albumin. PSNE were vaporized using a 30-cycle, 3.2-MHz, at an acoustic power of 6.4 W (free-field intensity of 4,586 W/cm(2)) pulse from a single-element, focused high-power transducer. The vaporization pulse was immediately followed by a 15-s continuous wave, 3.2-MHz signal to induce ultrasound-mediated heating. Control experiments were conducted using an identical procedure without the vaporization pulse. Lesion formation was detected by acquiring video frames during sonication and post-processing the images for analysis. Broadband emissions from inertial cavitation (IC) were passively detected with a focused, 2-MHz transducer. Temperature measurements were acquired using a needle thermocouple. RESULTS: Bubbles formed at the HIFU focus via PSNE vaporization enhanced HIFU-mediated heating. Broadband emissions detected during HIFU exposure coincided in time with measured accelerated heating, which suggested that IC played an important role in bubble-enhanced heating. In the presence of bubbles, the acoustic power required for the formation of a 9-mm(3) lesion was reduced by 72% and the exposure time required for the onset of albumin denaturation was significantly reduced (by 4 s), provided that the PSNE volume fraction in the polyacrylamide gel was at least 0.008%. CONCLUSIONS: The time or acoustic power required for lesion formation in gel phantoms was dramatically reduced by vaporizing PSNE into bubbles. These results suggest that PSNE may improve the efficiency of HIFU-mediated thermal ablation of solid tumors; thus, further investigation is warranted to determine whether bubble-enhanced HIFU may potentially become a viable option for cancer therapy.R21 EB009493 - NIBIB NIH HH

The Impact of Cultural Familiarity on Students’ Social Media Usage in Higher Education

Using social media (SM) in Higher education (HE) becomes unavoidable in the new teaching and learning pedagogy. The current generation of students creates their groups on SM for collaboration. However, SM can be a primary source of learning distraction due to its nature, which does not support structured learning. Hence, derived from the literature, this study proposes three learning customised system features, to be implemented on SM when used in Higher Education HE. Nevertheless, some psychological factors appear to have a stronger impact on students’ adoption of SM in learning than the proposed features. A Quantitative survey was conducted at a university in Uzbekistan to collect 52 undergraduate students’ perception of proposed SM learning customised features in Moodle. These features aim to provide localised, personalised, and privacy control self-management environment for collaboration in Moodle. These features could be significant in predicting students’ engagement with SM in HE. The data analysis showed a majority of positive feedback towards the proposed learning customised SM. However, the surveyed students’ engagement with these features was observed as minimal. The course leader initiated a semi-structured interview to investigate the reason. Although the students confirmed their acceptance of the learning customised features, their preferences to alternate SM, which is Telegram overridden their usage of the proposed learning customized SM, which is Twitter. The students avoided the Moodle integrated Twitter (which provided highly accepted features) and chose to use the Telegram as an external collaboration platform driven by their familiarity and social preferences with the Telegram since it is the popular SM in Uzbekistan. This study is part of an ongoing PhD research which involves deeper frame of learners’ cognitive usage of the learning management system. However, this paper exclusively discusses the cultural familiarity impact of student’s adoption of SM in HE

Giant Electron-hole Charging Energy Asymmetry in Ultra-short Carbon Nanotubes

Making full usage of bipolar transport in single-wall carbon nanotube (SWCNT) transistors could permit the development of two-in-one quantum devices with ultra-short channels. We report on clean $\sim$10 to 100 nm long suspended SWCNT transistors which display a large electron-hole transport asymmetry. The devices consist of naked SWCNT channels contacted with sections of SWCNT-under-annealed-gold. The annealed gold acts as an n-doping top gate which creates nm-sharp barriers at the junctions between the contacts and naked channel. These tunnel barriers define a single quantum dot (QD) whose charging energies to add an electron or a hole are vastly different ($e-h$ charging energy asymmetry). We parameterize the $e-h$ transport asymmetry by the ratio of the hole and electron charging energies $\eta_{e-h}$. We show that this asymmetry is maximized for short channels and small band gap SWCNTs. In a small band gap SWCNT device, we demonstrate the fabrication of a two-in-one quantum device acting as a QD for holes, and a much longer quantum bus for electrons. In a 14 nm long channel, $\eta_{e-h}$ reaches up to 2.6 for a device with a band gap of 270 meV. This strong $e-h$ transport asymmetry survives even at room temperature

Narrow scope for resolution-limit-free community detection

Detecting communities in large networks has drawn much attention over the years. While modularity remains one of the more popular methods of community detection, the so-called resolution limit remains a significant drawback. To overcome this issue, it was recently suggested that instead of comparing the network to a random null model, as is done in modularity, it should be compared to a constant factor. However, it is unclear what is meant exactly by "resolution-limit-free", that is, not suffering from the resolution limit. Furthermore, the question remains what other methods could be classified as resolution-limit-free. In this paper we suggest a rigorous definition and derive some basic properties of resolution-limit-free methods. More importantly, we are able to prove exactly which class of community detection methods are resolution-limit-free. Furthermore, we analyze which methods are not resolution-limit-free, suggesting there is only a limited scope for resolution-limit-free community detection methods. Finally, we provide such a natural formulation, and show it performs superbly

Testing Cluster Structure of Graphs

We study the problem of recognizing the cluster structure of a graph in the framework of property testing in the bounded degree model. Given a parameter $\varepsilon$, a $d$-bounded degree graph is defined to be $(k, \phi)$-clusterable, if it can be partitioned into no more than $k$ parts, such that the (inner) conductance of the induced subgraph on each part is at least $\phi$ and the (outer) conductance of each part is at most $c_{d,k}\varepsilon^4\phi^2$, where $c_{d,k}$ depends only on $d,k$. Our main result is a sublinear algorithm with the running time $\widetilde{O}(\sqrt{n}\cdot\mathrm{poly}(\phi,k,1/\varepsilon))$ that takes as input a graph with maximum degree bounded by $d$, parameters $k$, $\phi$, $\varepsilon$, and with probability at least $\frac23$, accepts the graph if it is $(k,\phi)$-clusterable and rejects the graph if it is $\varepsilon$-far from $(k, \phi^*)$-clusterable for $\phi^* = c'_{d,k}\frac{\phi^2 \varepsilon^4}{\log n}$, where $c'_{d,k}$ depends only on $d,k$. By the lower bound of $\Omega(\sqrt{n})$ on the number of queries needed for testing graph expansion, which corresponds to $k=1$ in our problem, our algorithm is asymptotically optimal up to polylogarithmic factors.Comment: Full version of STOC 201

Hadronic Gamma Rays from Supernova Remnants

A gas cloud near a supernova remnant (SNR) provides a target for pp-collisions leading to subsequent gamma-ray emission through neutral pion decay. The assumption of a power-law ambient spectrum of accelerated particles with index near -2 is usually built into models predicting the spectra of very-high energy (VHE) gamma-ray emission from SNRs. However, if the gas cloud is located at some distance from the SNR shock, this assumption is not necessarily correct. In this case, the particles which interact with the cloud are those leaking from the shock and their spectrum is approximately monoenergetic with the injection energy gradually decreasing as the SNR ages. In the GLAST energy range the gamma-ray spectrum resulting from particle interactions with the gas cloud will be flatter than expected, with the cutoff defined by the pion momentum distribution in the laboratory frame. We evaluate the flux of particles escaping from a SNR shock and apply the results to the VHE diffuse emission detected by the HESS at the Galactic centre.Comment: 4 pages, 3 figures. Contribution to the 30th ICRC, Merida, Mexico, 2007 (final version