A Bayesian Argumentation Framework for Distributed Fault Diagnosis in Telecommunication Networks

Traditionally, fault diagnosis in telecommunication network management is carried out by humans who use software support systems. The phenomenal growth in telecommunication networks has nonetheless triggered the interest in more autonomous approaches, capable of coping with emergent challenges such as the need to diagnose faults' root causes under uncertainty in geographically-distributed environments, with restrictions on data privacy. In this paper, we present a framework for distributed fault diagnosis under uncertainty based on an argumentative framework for multi-agent systems. In our approach, agents collaborate to reach conclusions by arguing in unpredictable scenarios. The observations collected from the network are used to infer possible fault root causes using Bayesian networks as causal models for the diagnosis process. Hypotheses about those fault root causes are discussed by agents in an argumentative dialogue to achieve a reliable conclusion. During that dialogue, agents handle the uncertainty of the diagnosis process, taking care of keeping data privacy among them. The proposed approach is compared against existing alternatives using benchmark multi-domain datasets. Moreover, we include data collected from a previous fault diagnosis system running in a telecommunication network for one and a half years. Results show that the proposed approach is suitable for the motivational scenario

Timeline of Adverse Events during Immune Checkpoint Inhibitors for Advanced Melanoma and Their Impacts on Survival

Immune-related adverse events (irAEs) are frequent and could be associated with improved response to immune checkpoint inhibitors (ICIs). A prospective cohort of advanced melanoma patients receiving ICI as first-line therapy was retrospectively reviewed (January 2011-February 2019). A total of 116 of 153 patients presented with at least one irAE (75.8%). The most frequent irAEs were dermatological (derm irAEs, 50%), asthenia (38%), and gastrointestinal (29%). Most irAEs appeared within the first 90 days, while 11.2% appeared after discontinuation of the therapy. Mild grade 1-2 derm irAEs tended to appear within the first 2 months of therapy with a median time of 65.5 days (IQR 26-139.25), while grade 3-4 derm irAEs appeared later (median 114 days; IQR 69-218) and could be detected at any time during therapy. Only derm irAE occurrence was related to improved survival (HR 6.46). Patients presenting derm irAEs showed better 5-year overall survival compared to those with no derm irAEs (53.1% versus 24.9%; p < 0.001). However, the difference was not significant when adjusting for the duration of therapy. In conclusion: the timeline of immune-related-AEs differs according to the organ involved. The (apparent) improved survival of patients who present derm AEs during immunotherapy could be partially explained by longer times under treatment

Demographic connectivity of sardine in the Bay of Biscay and Iberian coast region

Demographic connectivity in sardine populatio

CHAPTER 5: FORMATION AND EVOLUTION OF GALAXIES AND LARGE STRUCTURES

Peer reviewe

Testing the effects of opacity and the chemical mixture on the excitation of pulsations in B stars of the Magellanic Clouds

The B-type pulsators known as \beta Cephei and Slowly Pulsating B (SPB) stars present pulsations driven by the \kappa mechanism, which operates thanks to an opacity bump due to the iron group elements. In low-metallicity environments such as the Magellanic Clouds, \beta Cep and SPB pulsations are not expected. Nevertheless, recent observations show evidence for the presence of B-type pulsator candidates in both galaxies. We seek an explanation for the excitation of \beta Cep and SPB modes in those galaxies by examining basic input physics in stellar modelling: i) the specific metal mixture of B-type stars in the Magellanic Clouds; ii) the role of a potential underestimation of stellar opacities. We first derive the present-day chemical mixtures of B-type stars in the Magellanic Clouds. Then, we compute stellar models for that metal mixture and perform a non-adiabatic analysis of these models. In a second approach, we simulate parametric enhancements of stellar opacities due to different iron group elements. We then study their effects in models of B stars and their stability. We find that adopting a representative chemical mixture of B stars in the Small Magellanic Cloud cannot explain the presence of B-type pulsators there. An increase of the opacity in the region of the iron-group bump could drive B-type pulsations, but only if this increase occurs at the temperature corresponding to the maximum contribution of Ni to this opacity bump. We recommend an accurate computation of Ni opacity to understand B-type pulsators in the Small Magellanic Cloud, as well as the frequency domain observed in some Galactic hybrid \beta Cep-SPB stars.Comment: 16 pages, 12 figures. Accepted for publication in MNRA

Hierarchical Bayesian level set inversion

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to the length and amplitude scales in the prior probabilistic model. This paper demonstrates how the scale-sensitivity can be cir- cumvented by means of a hierarchical approach, using a single scalar parameter. Together with careful con- sideration of the development of algorithms which en- code probability measure equivalences as the hierar- chical parameter is varied, this leads to well-defined Gibbs based MCMC methods found by alternating Metropolis-Hastings updates of the level set function and the hierarchical parameter. These methods demon- strably outperform non-hierarchical Bayesian level set methods

Association of MC1R Variants and host phenotypes with melanoma risk in CDKN2A mutation carriers: a GenoMEL study

<p><b>Background</b> Carrying the cyclin-dependent kinase inhibitor 2A (CDKN2A) germline mutations is associated with a high risk for melanoma. Penetrance of CDKN2A mutations is modified by pigmentation characteristics, nevus phenotypes, and some variants of the melanocortin-1 receptor gene (MC1R), which is known to have a role in the pigmentation process. However, investigation of the associations of both MC1R variants and host phenotypes with melanoma risk has been limited.</p> <p><b>Methods</b> We included 815 CDKN2A mutation carriers (473 affected, and 342 unaffected, with melanoma) from 186 families from 15 centers in Europe, North America, and Australia who participated in the Melanoma Genetics Consortium. In this family-based study, we assessed the associations of the four most frequent MC1R variants (V60L, V92M, R151C, and R160W) and the number of variants (1, ≥2 variants), alone or jointly with the host phenotypes (hair color, propensity to sunburn, and number of nevi), with melanoma risk in CDKN2A mutation carriers. These associations were estimated and tested using generalized estimating equations. All statistical tests were two-sided.</p> <p><b>Results</b> Carrying any one of the four most frequent MC1R variants (V60L, V92M, R151C, R160W) in CDKN2A mutation carriers was associated with a statistically significantly increased risk for melanoma across all continents (1.24 × 10−6 ≤ P ≤ .0007). A consistent pattern of increase in melanoma risk was also associated with increase in number of MC1R variants. The risk of melanoma associated with at least two MC1R variants was 2.6-fold higher than the risk associated with only one variant (odds ratio = 5.83 [95% confidence interval = 3.60 to 9.46] vs 2.25 [95% confidence interval = 1.44 to 3.52]; Ptrend = 1.86 × 10−8). The joint analysis of MC1R variants and host phenotypes showed statistically significant associations of melanoma risk, together with MC1R variants (.0001 ≤ P ≤ .04), hair color (.006 ≤ P ≤ .06), and number of nevi (6.9 × 10−6 ≤ P ≤ .02).</p> <p><b>Conclusion</b> Results show that MC1R variants, hair color, and number of nevi were jointly associated with melanoma risk in CDKN2A mutation carriers. This joint association may have important consequences for risk assessments in familial settings.</p&gt