A novel experimental chamber for the characterization of free-falling particles in volcanic plumes.

Volcanic plumes pose a hazard to health and society and a particular risk for aviation. Hazard mitigation relies on forecasting plume dispersion within the atmosphere over time. The accuracy of forecasts depends on our understanding of particle dispersion and sedimentation processes, as well as on the accuracy of model input parameters, such as the initial particle size distribution and concentrations of volcanic particles (i.e., volcanic ash) in the atmosphere. However, our understating of these processes and the accurate quantification of input parameters remain the main sources of uncertainty in plume dispersion modeling. It is usually impractical to sample volcanic plumes directly, but particle sedimentation can be constrained in the laboratory. Here, we describe the design of a new experimental apparatus for investigating the dynamics of free-falling volcanic particles. The apparatus can produce a sustained column of falling particles with variable particle concentrations appropriate to a volcanic plume. Controllable experimental parameters include particle size distributions, types, and release rates. A laser-illuminated macrophotography system allows imaging of in-flight particles and their interactions. The mass of landing particles is logged to inform deposition rates. Quantitative measurements include particle morphology characterization, settling velocities, flow rates, and estimation of concentrations. Simultaneous observations of particle interaction processes and settling dynamics through direct control over a wide range of parameters will improve our parameterization of volcanic plume dynamics. Although the apparatus has been specifically designed for volcanological investigations, it can also be used to explore the characteristics of free-falling particle columns occurring in both environmental and industrial settings.

Challenges on the interaction of models and policy for pandemic control.

The COVID-19 pandemic has seen infectious disease modelling at the forefront of government decision-making. Models have been widely used throughout the pandemic to estimate pathogen spread and explore the potential impact of different intervention strategies. Infectious disease modellers and policymakers have worked effectively together, but there are many avenues for progress on this interface. In this paper, we identify and discuss seven broad challenges on the interaction of models and policy for pandemic control. We then conclude with suggestions and recommendations for the future.

Spatial Transmission Models: A Taxonomy and Framework.

Within risk analysis and, more broadly, the decision behind the choice of which modeling technique to use to study the spread of disease, epidemics, fires, technology, rumors, or, more generally, spatial dynamics, is not well documented. While individual models are well defined and the modeling techniques are well understood by practitioners, there is little deliberate choice made as to the type of model to be used, with modelers using techniques that are well accepted in the field, sometimes with little thought as to whether alternative modeling techniques could or should be used. In this article, we divide modeling techniques for spatial transmission into four main categories: population-level models, where a macro-level estimate of the infected population is required; cellular models, where the transmission takes place between connected domains, but is restricted to a fixed topology of neighboring cells; network models, where host-to-host transmission routes are modeled, either as planar spatial graphs or where shortcuts can take place as in social networks; and, finally, agent-based models that model the local transmission between agents, either as host-to-host geographical contacts, or by modeling the movement of the disease vector, with dynamic movement of hosts and vectors possible, on a Euclidian space or a more complex space deformed by the existence of information about the topology of the landscape. We summarize these techniques by introducing a taxonomy classifying these modeling approaches. Finally, we present a framework for choosing the most appropriate spatial modeling method, highlighting the links between seemingly disparate methodologies, bearing in mind that the choice of technique rests with the subject expert.

Radar micro-Doppler signatures of drones and birds at K-band and W-band.

Due to the substantial increase in the number of affordable drones in the consumer market and their regrettable misuse, there is a need for efficient technology to detect drones in airspace. This paper presents the characteristic radar micro-Doppler properties of drones and birds. Drones and birds both induce micro-Doppler signatures due to their propeller blade rotation and wingbeats, respectively. These distinctive signatures can then be used to differentiate a drone from a bird, along with studying them separately. Here, experimental measurements of micro-Doppler signatures of different types of drones and birds are presented and discussed. The data have been collected using two radars operating at different frequencies; K-band (24 GHz) and W-band (94 GHz). Three different models of drones and four species of birds of varying sizes have been used for data collection. The results clearly demonstrate that a phase coherent radar system can retrieve highly reliable and distinctive micro-Doppler signatures of these flying targets, both at K-band and W-band. Comparison of the signatures obtained at the two frequencies indicates that the micro-Doppler return from the W-band radar has higher SNR. However, micro-Doppler features in the K-band radar returns also reveal the micro-motion characteristics of drones and birds very effectively.

Topological isomorphisms of human brain and financial market networks.

Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimized for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets.

A kilowatt pulsed 94 GHz electron paramagnetic resonance spectrometer with high concentration sensitivity, high instantaneous bandwidth, and low dead time.

We describe a quasioptical 94 GHz kW pulsed electron paramagnetic resonance spectrometer featuring pi/2 pulses as short as 5 ns and an instantaneous bandwidth of 1 GHz in nonresonant sample holders operating in induction mode and at low temperatures. Low power pulses can be as short as 200 ps and kilowatt pulses as short as 1.5 ns with timing resolution of a few hundred picoseconds. Phase and frequency can be changed on nanosecond time scales and complex high power pulse sequences can be run at repetition rates up to 80 kHz with low dead time. We demonstrate that the combination of high power pulses at high frequencies and nonresonant cavities can offer excellent concentration sensitivity for orientation selective pulsed electron double resonance (double electron-electron resonance), where we demonstrate measurements at 1 microM concentration levels.

Immunomodulatory cytokines suppress epithelial nitric oxide production in inflammatory bowel disease by acting on mononuclear cells.

Inducible nitric oxide synthase (iNOS) activity in colonic epithelial HT-29 cells is modulated by the T-cell-derived cytokines IL-4 and IL-13, but is not affected by IL-10 despite its effect in models of colitis. We studied the effects of these cytokines on nitric oxide (NO) production by colonic tissue. IL-10 and IL-4 but not IL-13 suppressed the NO production and iNOS expression by inflamed tissue and cytokine-stimulated noninflamed tissue from patients with ulcerative colitis, whereas the three cytokines suppressed NO production in cytokine-stimulated biopsies from controls. To examine why colonic biopsies and HT-29 cells respond differently to immunomodulatory cytokines, a coculture of mixed mononuclear monocytes (MMC) and HT-29 cells was studied. Treatment of HT-29 cells with conditioned medium from IFN-gamma/LPS-stimulated MMC produced significant amounts of NO, which suggested the presence of an MMC-derived soluble factor modifying epithelial NO production. Pretreatment of IFN-gamma/LPS-stimulated MMC with IL-10 and IL-4 but not IL-13 suppressed NO production by HT-29 cells. Interestingly, pretreatment of HT-29 cells with IL-1 receptor antagonist suppressed the IFN-gamma/LPS-stimulated MMC-induced NO production. These results suggest that immunomodulatory cytokines might exert an inhibitory effect on NO up-regulation by colonic epithelium via the inhibition of MMC-derived soluble mediators, such as IL-1.

Effect of corticosteroids on nitric oxide production in inflammatory bowel disease: are leukocytes the site of action?

Nitric oxide (NO) production is increased in the human colonic mucosa in intestinal inflammation. We examined the effect of corticosteroids and the role of mononuclear cells in this production. Colonic biopsies from patients with ulcerative colitis and normal controls were cultured with either budesonide or prednisolone in the presence of proinflammatory cytokines. Human mixed mononuclear cells (MMCs) were cocultured with HT-29 cells stimulated with IFN-gamma and LPS in the presence or absence of corticosteroids. Nitrite production was measured in supernatants by a modification of the Griess reaction, and inducible NO synthase (iNOS) mRNA expression was studied in colonic tissue by RT-PCR. Both steroids significantly suppressed the nitrite production and iNOS mRNA expression in inflamed colonic biopsies from ulcerative colitis patients and in cytokine-stimulated normal colonic biopsies but not in cytokine-stimulated HT-29 cells. Nitrite production by HT-29 cells was significantly increased (P < 0.01) in cocultures with MMCs stimulated with IFN-gamma and LPS. The presence of either prednisolone or budesonide significantly (P < 0.01) suppressed nitrite production from cocultures of HT-29 cells and MMCs but not from cultures of HT-29 cells stimulated with conditioned media from activated MMCs. Interestingly, stimulation of HT-29 with conditioned media from MMCs pretreated with steroids before stimulation with LPS and IFN-gamma induced a significantly (P < 0.01) lower nitrite production. These results suggest that the inhibitory effect of corticosteroids on the NO production in the intestinal inflammation might be via the inhibition of MMC-produced mediators responsible for NO production by colonic epithelial cells.

Differential regulation of prostaglandin E biosynthesis by interferon-gamma in colonic epithelial cells.

1. Cyclooxygenase (COX)-2 expression and activity in response to pro-inflammatory cytokines TNF alpha and IFN gamma was evaluated in the colonic epithelial cell line HT29 and the airway epithelial cell line A549. 2. TNF alpha induced concentration- and time-dependent upregulation of COX-2 mRNA, protein and prostaglandin (PG)E(2) synthesis. 3. Co-stimulation of TNF alpha with IFN gamma resulted in reduced COX-2 mRNA and protein expression. 4. IFN gamma had no effect on the stability of TNF alpha-induced COX-2 mRNA. 5. TNF alpha-induced PGE(2) biosynthesis was significantly enhanced by the simultaneous addition of IFN gamma and was COX-2 dependent. 6. The combination of IFN gamma and TNF alpha induced the microsomal prostaglandin E synthase (mPGES), comensurate with the enhanced PGE(2) synthesis. 7. These results suggest that, in terms of PGE(2) biosynthesis, IFN gamma plays a negative regulatory role at the level of COX-2 expression and a positive regulatory role at the level of mPGES expression. This may have important implications for the clinical use of IFN gamma in inflammatory diseases.