Cavity effect in the quasinormal mode spectrum of topological stars

We study scalar perturbations of topological solitons, smooth horizonless solutions in five-dimensional Einstein-Maxwell theory that correspond to coherent states of gravity via the dynamics of extra compact dimensions. First, we compute scalar quasinormal modes for topological stars that have a single unstable photon sphere, and we show that the spectrum is very similar to that of a black hole with the same photon sphere. Next, we study topological stars that have both a stable inner photon sphere and an unstable one. The first few quasinormal modes are localized around the inner photon sphere. The spectrum also contains ''black-hole like modes'' localized at the unstable outer photon sphere. The frequencies of these modes are similar to those of a black hole, but their imaginary part is smaller due to a cavity effect associated with the inner photon sphere. The longer damping produced by this trapping effect may have implications for black hole spectroscopy.Comment: 17 pages + Appendix, 11 figure

Evaluation of pyrrolidine and pyrazolone derivatives as inhibitors of trypanosomal phosphodiesterase B1 (TbrPDEB1)

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Tetrahedron Letters 56 (2015): 2832-2835, doi:10.1016/j.tetlet.2015.04.061.Human African trypanosomiasis (HAT) is a parasitic disease, caused by the protozoan pathogen Trypanosoma brucei, which affects thousands every year and which is in need of new therapeutics. Herein we report the synthesis and assessment of a series of pyrrolidine and pyrazolone derivatives of human phosphodiesterase 4 (hPDE4) inhibitors for the assessment of their activity against the trypanosomal phosphodiesterase TbrPDEB1. The synthesized compounds showed weak potency against TbrPDEB1.We acknowledge funding from the National Institutes of Health (R01AI082577)

Advances in Marine Ecosystem Dynamics from US GLOBEC: The Horizontal-Advection Bottom-up Forcing Paradigm

A primary focus of the US Global Ocean Ecosystem Dynamics (GLOBEC) program was to identify the mechanisms of ecosystem response to large- scale climate forcing under the assumption that bottom-up forcing controls a large fraction of marine ecosystem variability. At the beginning of GLOBEC, the prevailing bottom-up forcing hypothesis was that climate-induced changes in vertical transport modulated nutrient supply and surface primary productivity, which in turn affected the lower trophic levels (e.g., zooplankton) and higher trophic levels (e.g., fish) through the trophic cascade. Although upwelling dynamics were confirmed to be an important driver of ecosystem variability in GLOBEC studies, the use of eddy- resolving regional-scale ocean circulation models combined with field observations revealed that horizontal advection is an equally important driver of marine ecosystem variability. Trough a synthesis of studies from the four US GLOBEC regions (Gulf of Alaska, Northern California Current, Northwest Atlantic, and Southern Ocean), a new horizontal-advection bottom-up forcing paradigm emerges in which large-scale climate forcing drives regional changes in alongshore and cross-shelf ocean transport that directly impact ecosystem functions (e.g., productivity, species composition, spatial connectivity). Te horizontal advection bottom-up forcing paradigm expands the mechanistic pathways through which climate variability and climate change impact the marine ecosystem. In particular, these results highlight the need for future studies to resolve and understand the role of mesoscale and submesoscale transport processes and their relationship to climate

IoT vulnerability data crawling and analysis

Internet of Things (IoT) is a whole new ecosystem comprised of heterogeneous connected devices —i.e. computers, laptops, smart-phones and tablets as well as embedded devices and sensors— that communicate to deliver capabilities making our living, cities, transport, energy, and many other areas more intelligent. The main concerns raised from the IoT ecosystem are the devices poor support for patching/updating and the poor on-board computational power. A number of issues stem from this: inherent vulnerabilities and the inability to detect and defend against external attacks. Also, due to the nature of their operation, the devices tend to be rather open to communication, which makes attacks easy to spread once reaching a network. The aim of this research is to investigate if it is possible to extract useful results regarding attacks’ trends and be able to predict them, before it is too late, by crawling Deep/Dark and Surface web. The results of this work show that is possible to find the trend and be able to act proactively in order to protect the IoT ecosystem

Repurposing human PDE4 inhibitors for neglected tropical diseases : design, synthesis and evaluation of cilomilast analogues as Trypanosoma brucei PDEB1 inhibitors

Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Bioorganic & Medicinal Chemistry Letters 24 (2014): 4084-4089, doi:10.1016/j.bmcl.2014.07.063.A medicinal chemistry exploration of the human phosphodiesterase 4 (hPDE4) inhibitor cilomilast (1) was undertaken in order to identify inhibitors of phosphodiesterase B1 of Trypanosoma brucei (TbrPDEB1). T. brucei is the parasite which causes African sleeping sickness, a neglected tropical disease that affects thousands each year, and TbrPDEB1 has been shown to be an essential target of therapeutic relevance. Noting that 1 is a weak inhibitor of TbrPDEB1, we report the design and synthesis of analogs of this compound, culminating in 12b, a sub-micromolar inhibitor of TbrPDEB1 that shows modest inhibition of T. brucei proliferation.This work was funded by the National Institutes of Health (R01AI082577)

Recurrent Neural Networks for Daily Estimation of COVID-19 Prognosis with Uncertainty Handling

Most ML-based applications for COVID-19 assess the general conditions of a patient trained and tested on cohorts of patients collected over a short period of time and are capable of providing an alarm a few days in advance, helping clinicians in emergency situations, monitor hospitalised patients and identify potentially critical situations at an early stage. However, the pandemic continues to evolve due to new variants, treatments, and vaccines; considering datasets over short periods could not capture this aspect. In addition, these applications often avoid dealing with the uncertainty associated with the prediction provided by machine learning models, potentially causing costly mistakes. In this work, we present a system based on Recurrent Neural Networks (RNN) for the daily estimate of the prognosis of COVID-19 patients that is built and tested using data collected over a long period of time. Our system achieves high predictive performance and uses an algorithm to effectively determine and discard those patients for whom RNN cannot predict the prognosis with sufficient confidence

Direct Nano-Imaging of Light-Matter Interactions in Nanoscale Excitonic Emitters

Strong light-matter interactions in localized nano-emitters when placed near metallic mirrors have been widely reported via spectroscopic studies in the optical far-field. Here, we report a near-field nano-spectroscopic study of the localized nanoscale emitters on a flat Au substrate. We observe strong-coupling of the excitonic dipoles in quasi 2-dimensional CdSe/CdxZnS1-xS nanoplatelets with gap mode plasmons formed between the Au tip and substrate. We also observe directional propagation on the Au substrate of surface plasmon polaritons launched from the excitons of the nanoplatelets as wave-like fringe patterns in the near-field photoluminescence maps. These fringe patterns were confirmed via extensive electromagnetic wave simulations to be standing-waves formed between the tip and the emitter on the substrate plane. We further report that both light confinement and the in-plane emission can be engineered by tuning the surrounding dielectric environment of the nanoplatelets. Our results lead to renewed understanding of in-plane, near-field electromagnetic signal transduction from the localized nano-emitters with profound implications in nano and quantum photonics as well as resonant optoelectronics.Comment: manuscript + supporting informatio