| 1. |
- Surendran, Praveen, et al.
(author)
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Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals
- 2020
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 52:12, s. 1314-1332
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Journal article (peer-reviewed)abstract
- Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency <= 0.01) variant BP associations (P < 5 x 10(-8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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| 2. |
- Alisic, Rijad, et al.
(author)
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Ensuring privacy of occupancy changes in smart buildings
- 2020
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In: CCTA 2020 - 4th IEEE Conference on Control Technology and Applications. - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 871-876
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Conference paper (peer-reviewed)abstract
- Smart building management systems rely on sensors to optimize the operation of buildings. If an unauthorized user gains access to these sensors, a privacy leak may occur. This paper considers such a potential leak of privacy in a smart residential building, and how it may be mitigated by corrupting the measurements with additive Gaussian noise. This corruption is done in order to hide when the occupancy changes in an apartment. A lower bound on the variance of any estimator that estimates the change time is derived. The bound is then used to analyze how different model parameters affect the variance. It is shown that the signal to noise ratio and the system dynamics are the main factors that affect the bound. These results are then verified on a simulator of the KTH Live-In Lab Testbed, showing good correspondence with theoretical results.
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| 3. |
- Janson, Axel, et al.
(author)
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Analysis of a Networked SIS Multi-Virus Model with a Shared Resource
- 2020
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In: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 797-802
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Conference paper (peer-reviewed)abstract
- In this paper, we introduce a continuous-time competing virus model with a shared resource. We say that the system is in the healthy state if all the agents are healthy, and the shared resource is not contaminated. If the epidemic remains persistent, and the shared resource is contaminated, we say that the system is in the endemic state. First of all we show, under appropriate assumptions, that the model we introduce is well-posed. Secondly, we establish sufficient conditions for exponential (resp. asymptotic) eradication of a virus. Thirdly, for the single-virus case with a shared resource, we establish conditions that lead to existence of an endemic equilibrium. Finally, we provide a necessary and sufficient condition for uniqueness of the healthy state.
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| 4. |
- Pare, Philip E., et al.
(author)
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Analysis, Online Estimation, and Validation of a Competing Virus Model
- 2020
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In: 2020 American Control Conference (ACC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 2556-2561
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Conference paper (peer-reviewed)abstract
- In this paper we introduce a discrete time competing virus model and the assumptions necessary for the model to be well posed. We analyze the system exploring its different equilibria. We provide necessary and sufficient conditions for the estimation of the model parameters from time series data and introduce an online estimation algorithm. We employ a dataset of two competing subsidy programs from the US Department of Agriculture to validate the model by employing the identification techniques. To the best of our knowledge, this work is the first to study competing virus models in discretetime, online identification of spread parameters from time series data, and validation of said models using real data. These new contributions are important for applications since real data is naturally sampled.
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| 5. |
- Ruf, Sebastian F., et al.
(author)
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Going Viral : Stability of Consensus-Driven Adoptive Spread
- 2020
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In: IEEE Transactions on Network Science and Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4697. ; 7:3, s. 1764-1773
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Journal article (peer-reviewed)abstract
- The spread of new products in a networked population is often modeled as an epidemic. However, in the case of "complex" contagion, these models do not capture nuanced, dynamic social reinforcement effects in adoption behavior. In this paper, we investigate a model of complex contagion which allows a coevolutionary interplay between adoption, modeled as an SIS epidemic spreading process, and social reinforcement effects, modeled as consensus opinion dynamics. Asymptotic stability analysis of the all-adopt as well as the none-adopt equilibria of the combined opinion-adoption model is provided through the use of Lyapunov arguments. In doing so, sufficient conditions are provided which determine the stability of the "flop" state, where no one adopts the product and everyone's opinion of the product is least favorable, and the "hit" state, where everyone adopts and their opinions are most favorable. These conditions are shown to extend to the bounded confidence opinion dynamic under a stronger assumption on the model parameters. Additional analysis is provided for the case where the product is neither a hit nor a flop. To conclude, numerical simulations demonstrate behaviors indicated in the sociology literature such as tipping points.
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| 6. |
- Vrabac, Damir, et al.
(author)
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Overcoming Challenges for Estimating Virus Spread Dynamics from Data
- 2020
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In: Proceedings of the 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020. - : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- In this paper we investigate estimating the parameters of a discrete time networked virus spread model from time series data. We explore the effect of multiple challenges on the estimation process including system noise, missing data, time-varying network structure, and quantization of the measurements. We also demonstrate how well a heterogeneous model can be captured by homogeneous model parameters. We further illustrate these challenges by employing recent data collected from the ongoing 2019 novel coronavirus (2019-nCoV) outbreak, motivating future work.
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| 7. |
- Wang, Dan, et al.
(author)
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Controlling a Networked SIS Model via a Single Input over Undirected Graphs
- 2020
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In: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 10981-10986
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Conference paper (peer-reviewed)abstract
- This paper formulates and studies the problem of controlling a networked SIS model using a single input in which the network structure is described by a connected undirected graph. A necessary and sufficient condition on the values of curing and infection rates for the healthy state to be exponentially stable is obtained via the analysis of signed Laplacians when the control input is the curing budget of a single agent. In the case when the healthy state is stabilizable, an explicit expression for the minimum curing budget is provided. The utility of the algorithm is demonstrated using a simulation over a network of cities in the northeastern United States.
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| 8. |
- Xuan, Weihao, et al.
(author)
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On a Network SIS Model with Opinion
- 2020
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In: Proceedings 21st IFAC World Congress on Automatic Control. - : Elsevier BV. ; , s. 2582-2587
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Conference paper (peer-reviewed)abstract
- This paper proposes a network continuous-time susceptible-infected-susceptible (SIS) model coupled with individual opinion dynamics, where the opinion dynamics models an individual's perceived severity of illness or perceived susceptibility. The effects of opinion dynamics on the network SIS model are studied by analyzing the limiting behaviors of the system model, equilibria of the system and their stability.
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