Multiscale Analysis of Spreading in a Large Communication Network

In temporal networks, both the topology of the underlying network and the timings of interaction events can be crucial in determining how some dynamic process mediated by the network unfolds. We have explored the limiting case of the speed of spreading in the SI model, set up such that an event between an infectious and susceptible individual always transmits the infection. The speed of this process sets an upper bound for the speed of any dynamic process that is mediated through the interaction events of the network. With the help of temporal networks derived from large scale time-stamped data on mobile phone calls, we extend earlier results that point out the slowing-down effects of burstiness and temporal inhomogeneities. In such networks, links are not permanently active, but dynamic processes are mediated by recurrent events taking place on the links at specific points in time. We perform a multi-scale analysis and pinpoint the importance of the timings of event sequences on individual links, their correlations with neighboring sequences, and the temporal pathways taken by the network-scale spreading process. This is achieved by studying empirically and analytically different characteristic relay times of links, relevant to the respective scales, and a set of temporal reference models that allow for removing selected time-domain correlations one by one

Dynamics of genotype-specific HPV clearance and reinfection in rural Ghana may compromise HPV screening approaches

Persistent Human Papillomavirus (HPV) infection is a prerequisite for cervical cancer development. Few studies investigated clearance of high-risk HPV in low-and-middle-income countries. Our study investigated HPV clearance and persistence over four years in women from North Tongu District, Ghana. In 2010/2011, cervical swabs of 500 patients were collected and HPV genotyped (nested multiplex PCR) in Accra, Ghana. In 2014, 104 women who previously tested positive for high-risk HPV and remained untreated were re-tested for HPV. Cytobrush samples were genotyped (GP5+/6+ PCR & Luminex-MPG readout) in Berlin, Germany. Positively tested patients underwent colposcopy and treatment if indicated. Of 104 women, who tested high-risk HPV+ in 2010/2011, seven (6,7%; 95%CI: 2.7-13.4%) had ≥1 persistent high-risk-infection after ~4 years (mean age 39 years). Ninety-seven (93,3%; 95%CI: 86.6-97.3%) had cleared the original infection, while 22 (21.2%; 95%CI: 13.8-30.3%) had acquired new high-risk infections with other genotypes. Persistent types found were HPV 16, 18, 35, 39, 51, 52, 58, and 68. Among those patients, one case of CIN2 (HPV 68) and one micro-invasive cervical cancer (HPV 16) were detected. This longitudinal observational data suggest that single HPV screening rounds may lead to over-referral. Including type-specific HPV re-testing or additional triage methods could help reduce follow-up rates

New constraints on supersymmetry using neutrino telescopes

We demonstrate that megaton-mass neutrino telescopes are able to observe the signal from long-lived particles beyond the Standard Model, in particular the stau, the supersymmetric partner of the tau lepton. Its signature is an excess of charged particle tracks with horizontal arrival directions and energy deposits between 0.1 and 1 TeV inside the detector. We exploit this previously-overlooked signature to search for stau particles in the publicly available IceCube data. The data shows no evidence of physics beyond the Standard Model. We derive a new lower limit on the stau mass of 320 GeV (95% C.L.) and estimate that this new approach, when applied to the full data set available to the IceCube collaboration, will reach word-leading sensitivity to the stau mass (m_{\tilde{t}} = 450GeV)

Towards space based verification of CO₂ emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation

Carbon dioxide (CO₂) is the most important man-made greenhouse gas (GHG) that cause global warming. With electricity generation through fossil-fuel power plants now being the economic sector with the largest source of CO₂, power plant emissions monitoring has become more important than ever in the fight against global warming. In a previous study done by Bovensmann et al. (2010), random and systematic errors of power plant CO₂ emissions have been quantified using a single overpass from a proposed CarbonSat instrument. In this study, we quantify errors of power plant annual emission estimates from a hypothetical CarbonSat and constellations of several CarbonSats while taking into account that power plant CO₂ emissions are time-dependent. Our focus is on estimating systematic errors arising from the sparse temporal sampling as well as random errors that are primarily dependent on wind speeds. We used hourly emissions data from the US Environmental Protection Agency (EPA) combined with assimilated and re-analyzed meteorological fields from the National Centers of Environmental Prediction (NCEP). CarbonSat orbits were simulated as a sun-synchronous low-earth orbiting satellite (LEO) with an 828-km orbit height, local time ascending node (LTAN) of 13:30 (01:30 p.m. LT) and achieves global coverage after 5 days. We show, that despite the variability of the power plant emissions and the limited satellite overpasses, one CarbonSat has the potential to verify reported US annual CO₂ emissions from large power plants (≥5 Mt CO₂ yr⁻¹) with a systematic error of less than ~4.9% and a random error of less than ~6.7% for 50% of all the power plants. For 90% of all the power plants, the systematic error was less than ~12.4% and the random error was less than ~13%. We additionally investigated two different satellite configurations using a combination of 5 CarbonSats. One achieves global coverage everyday but only samples the targets at fixed local times. The other configuration samples the targets five times at two-hour intervals approximately every 6th day but only achieves global coverage after 5 days. From the statistical analyses, we found, as expected, that the random errors improve by approximately a factor of two if 5 satellites are used. On the other hand, more satellites do not result in a large reduction of the systematic error. The systematic error is somewhat smaller for the CarbonSat constellation configuration achieving global coverage everyday. Therefore, we recommend the CarbonSat constellation configuration that achieves daily global coverage

Partial “targeted” embolisation of brain arteriovenous malformations

The treatment of pial arteriovenous brain malformations is controversial. Little is yet known about their natural history, their pathomechanisms and the efficacy and risks of respective proposed treatments. It is known that only complete occlusion of the AVM can exclude future risk of haemorrhage and that the rates of curative embolisation of AVMs with an acceptable periprocedural risk are around 20 to 50%. As outlined in the present article, however, partial, targeted embolisation also plays a role. In acutely ruptured AVMs where the source of bleeding can be identified, targeted embolisation of this compartment may be able to secure the AVM prior to definitive treatment. In unruptured symptomatic AVMs targeted treatment may be employed if a defined pathomechanism can be identified that is related to the clinical symptoms and that can be cured with an acceptable risk via an endovascular approach depending on the individual AVM angioarchitecture. This review article gives examples of pathomechanisms and angioarchitectures that are amenable to this kind of treatment strategy

MAMAP – a new spectrometer system for column-averaged methane and carbon dioxide observations from aircraft: instrument description and performance analysis

Abstract. Carbon dioxide (CO2) and Methane (CH4) are the two most important anthropogenic greenhouse gases. CH4 is furthermore one of the most potent present and future contributors to global warming because of its large global warming potential (GWP). Our knowledge of CH4 and CO2 source strengths is based primarily on bottom-up scaling of sparse in-situ local point measurements of emissions and up-scaling of emission factor estimates or top-down modeling incorporating data from surface networks and more recently also by incorporating data from low spatial resolution satellite observations for CH4. There is a need to measure and retrieve the dry columns of CO2 and CH4 having high spatial resolution and spatial coverage. In order to fill this gap a new passive airborne 2-channel grating spectrometer instrument for remote sensing of small scale and mesoscale column-averaged CH4 and CO2 observations has been developed. This Methane Airborne MAPper (MAMAP) instrument measures reflected and scattered solar radiation in the short wave infrared (SWIR) and near-infrared (NIR) parts of the electro-magnetic spectrum at moderate spectral resolution. The SWIR channel yields measurements of atmospheric absorption bands of CH4 and CO2 in the spectral range between 1.59 and 1.69 μm at a spectral resolution of 0.82 nm. The NIR channel around 0.76 μm measures the atmospheric O2-A-band absorption with a resolution of 0.46 nm. MAMAP has been designed for flexible operation aboard a variety of airborne platforms. The instrument design and the performance of the SWIR channel, together with some results from on-ground and in-flight engineering tests are presented. The SWIR channel performance has been analyzed using a retrieval algorithm applied to the nadir measured spectra. Dry air column-averaged mole fractions are obtained from SWIR data only by dividing the retrieved CH4 columns by the simultaneously retrieved CO2 columns for dry air column CH4 (XCH4) and vice versa for dry air column CO2 (XCO2). The signal-to-noise ratio (SNR) of the SWIR channel is approximately 1000 for integration times (tint) in the range of 0.6–0.8 s for scenes with surface spectral reflectances (SSR)/albedo of around 0.18. At these integration times the ground scene size is about 23 × 33 m2 for an aircraft altitude of 1 km and a ground speed of 200 km/h. For these scenes the actual XCH4 or XCO2 dry air column retrieval precisions are typically about 1% (1 σ). Elevated levels of CH4 have been retrieved above a CH4 emitting landfill. Similarly the plume of CO2 from coal-fired power plants can be well detected and tracked. The measurements by the MAMAP sensor could enable estimates of anthropogenic, biogenic and geological emissions of localized intense CH4 and CO2 sources such as anthropogenic fugitive CH4 emissions from oil and gas industry, coal mining, disposal of organic waste, CO2 emissions from coal-fired power plants, steel production or geologic CH4 and CO2 emissions from seepage and volcanoes. Appropriate analysis of the measurements of MAMAP potentially also yields natural CH4 emissions from less intense but extensive sources such as wetlands

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.Comment: 11 pages, 15 figure