Robust Report Level Cluster-to-Track Fusion

In this paper we develop a method for report level tracking based on Dempster-Shafer clustering using Potts spin neural networks where clusters of incoming reports are gradually fused into existing tracks, one cluster for each track. Incoming reports are put into a cluster and continuous reclustering of older reports is made in order to obtain maximum association fit within the cluster and towards the track. Over time, the oldest reports of the cluster leave the cluster for the fixed track at the same rate as new incoming reports are put into it. Fusing reports to existing tracks in this fashion allows us to take account of both existing tracks and the probable future of each track, as represented by younger reports within the corresponding cluster. This gives us a robust report-to-track association. Compared to clustering of all available reports this approach is computationally faster and has a better report-to-track association than simple step-by-step association.Comment: 6 pages, 5 figure

A Young Solar Twin in the Rosette Cluster NGC 2244 Line of Sight

Based on prior precision photometry and cluster age analysis, the bright star GSC 00154−01819 is a possible young pre-main sequence member of the Rosette cluster, NGC 2244. As part of a comprehensive study of the large-scale structure of the Rosette and its excitation by the cluster stars, we noted this star as a potential backlight for a probe of the interstellar medium and extinction along the sight line towards a distinctive nebular feature projected on to the cluster centre. New high-resolution spectra of the star were taken with the University College London Echelle Spectrograph of the AAT. They reveal that rather than being a reddened spectral type B or A star within the Mon OB2 association, it is a nearby, largely unreddened, solar twin of spectral type G2V less than 180 Myr old. It is about 219 pc from the Sun with a barycentric radial velocity of +14.35 ± 1.99 km s−1. The spectrum of the Rosette behind it and along this line of sight shows a barycentric radial velocity of +26.0 ± 2.4 km s−1 in H α, and a full width at half-maximum velocity dispersion of 61.94 ± 1.38 km s−1

A phase-resolved XMM-Newton Campaign on the Colliding Wind Binary HD 152248

We report the first results of an XMM-Newton monitoring campaign of the NGC 6231 open cluster in the Sco OB1 association. This first paper focuses on the massive colliding wind binary HD 152248, which is the brightest X-ray source of the cluster. The campaign, with a total duration of 180 ksec, was split into six separate observations, following the orbital motion of HD 152248. The X-ray flux from this system presents a clear, asymmetric modulation with the phase and ranges from 0.73 to 1.18 10-12 erg s-1 cm-2 in the [0.5-10.0 keV] energy band. The maximum of the emission is reached slightly after apastron. The EPIC spectra are quite soft and peak around 0.8-0.9 keV. We characterize their shape using several combinations of mekal models and power-law spectra and we detect significant spectral variability in the [0.5-2.5 keV] energy band. We also perform 2-D hydrodynamical simulations using different sets of parameters that closely reproduce the physical and orbital configuration of the HD 152248 system at the time of the six XMM-Newton pointings. This allows a direct confrontation of the model predictions with the constraints deduced from the X-ray observations of the system. We show that the observed variation of the flux can be explained by a variation of the X-ray emission from the colliding wind zone, diluted by the softer X-ray contribution of the two O-type stars of the system. Our simulations also reveal that the interaction region of HD 152248 should be highly unstable, giving rise to shells of dense gas that are separated by low density regions. Finally, we perform a search for short-term variability in the light curves of the system and we show that trends are present within several of the 30 ksec exposures of our campaign. Further, most of these trends are in good .Comment: Accepted by MNRAS; 22 pages; without figures; complete PS version (including figures) on http://vela.astro.ulg.ac.be/Preprints/index.htm

Evaluation by Geospatial and Spatiotemporal Distribution of Tularemia Cases in Arkansas

Tularemia is a vector-borne disease of global concern with diverse regional foci. Arkansas is an endemic state with differences in case distribution and land suitability supporting host and vector sustainment. The aim of this study was to conduct a geospatial and spatiotemporal assessment of factors associated with case distribution and timeliness and completeness of public reporting. Guided with direction from spatial epidemiology and nidality, referring to the association of ecology, climate, and proximity of disease, analysis included secondary data collected from the Arkansas Department of Health between 1995 and 2018. Using Poisson-based software, 2 clusters were found: a high-risk cluster encompassing 23% of the total population within 24 counties spanning an 8-year period (RR = 4.98, p \u3c 0.05), and a low risk cluster that included 25% of the population within 28 counties during a 12-year period (RR 0.14, p \u3c 0.05). Analysis of ecological data revealed associations between annual precipitation within the high-risk cluster and total number of cases (AUC = 0.716 and AUC = 0.726, respectively) with trends toward higher incidence rates in suitable land cover and moderate to high elevation using maximum entropy software. Analysis of timeliness and completeness revealed gaps for clinical form and transmission mode determination (p \u3c 0.05), while increases in probable cases followed decreases in confirmed cases revealing gaps in laboratory diagnostics. Positive social change necessitates multidisciplinary collaboration between climatologists, clinicians, and epidemiologists to reach high-risk populations and promote educational awareness. The potential for social change includes predictive modeling optimizing funding while representing underserved populations

Spectral Efficient and Energy Aware Clustering in Cellular Networks

The current and envisaged increase of cellular traffic poses new challenges to Mobile Network Operators (MNO), who must densify their Radio Access Networks (RAN) while maintaining low Capital Expenditure and Operational Expenditure to ensure long-term sustainability. In this context, this paper analyses optimal clustering solutions based on Device-to-Device (D2D) communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced Clustering Optimization for Resources' Efficiency (eCORE) is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as Clustering algorithm for Load Balancing (CaLB), is also proposed to create non-spectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the Clustering Energy Efficient algorithm (CEEa) is also designed to manage the trade-off between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption

Quasichemical theory and the description of associating fluids relative to a reference: Multiple bonding of a single site solute

We derive an expression for the chemical potential of an associating solute in a solvent relative to the value in a reference fluid using the quasichemical organization of the potential distribution theorem. The fraction of times the solute is not associated with the solvent, the monomer fraction, is expressed in terms of (a) the statistics of occupancy of the solvent around the solute in the reference fluid and (b) the Widom factors that arise because of turning on solute-solvent association. Assuming pair-additivity, we expand the Widom factor into a product of Mayer f-functions and the resulting expression is rearranged to reveal a form of the monomer fraction that is analogous to that used within the statistical associating fluid theory (SAFT). The present formulation avoids all graph-theoretic arguments and provides a fresh, more intuitive, perspective on Wertheim's theory and SAFT. Importantly, multi-body effects are transparently incorporated into the very foundations of the theory. We illustrate the generality of the present approach by considering examples of multiple solvent association to a colloid solute with bonding domains that range from a small patch on the sphere, a Janus particle, and a solute whose entire surface is available for association