A reversible infinite HMM using normalised random measures

We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.Comment: 9 pages, 6 figure

Bayesian nonparametrics for Sparse Dynamic Networks

We propose a Bayesian nonparametric prior for time-varying networks. To each node of the network is associated a positive parameter, modeling the sociability of that node. Sociabilities are assumed to evolve over time, and are modeled via a dynamic point process model. The model is able to (a) capture smooth evolution of the interaction between nodes, allowing edges to appear/disappear over time (b) capture long term evolution of the sociabilities of the nodes (c) and yield sparse graphs, where the number of edges grows subquadratically with the number of nodes. The evolution of the sociabilities is described by a tractable time-varying gamma process. We provide some theoretical insights into the model and apply it to three real world datasets.Comment: 10 pages, 8 figure

A simulator for a mobile peer-to-peer database environment

We present a simulation environment that can be employed to study P2P mobile networks that are fast-evolving in both their topology and their content. This simulator implements a proposed P2P architecture based on Mobile Agent and Active Database technology and can be employed in order to build simulated mobile networks that are characterized by a diversity in peer needs, specifications and capabilities

Possible COVID-19-Associated Pulmonary Aspergillosis Due to <i>Aspergillus niger</i> in Greece

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes direct damage to the pulmonary epithelium, enabling Aspergillus invasion. Rapid progression and high mortality of invasive aspergillosis have been reported. In the present study, we report a rare case of possible COVID-19-associated pulmonary aspergillosis (CAPA) caused by A. niger in a Greek patient. Diagnosis was based on ECMM/ISHAM specific criteria and the new algorithm “BM-AspICU” for the invasive pulmonary aspergillosis diagnostic strategy. The fungal isolate was recovered in a non-bronchoalveolar lavage (non-BAL) sample and its identification was performed by standard macroscopic and microscopic morphological studies. MALDI-TOF analysis confirmed the identification of A. niger. In addition, galactomannan antigen and Aspergillus real-time PCR testing were positive in the non-BAL sample, while in serum they proved negative. The A. niger isolate showed an MIC for fluconazole ≥128 μg/mL, for itraconazole and posaconazole 0.25 μg/mL, for voriconazole 0.5 μg/mL, for flucytosine 4 μg/mL, for amphotericin B 1 μg/mL, and for all echinocandins (caspofungin, anidulafungin, micafungin) >8 μg/mL. The patient was initially treated with voriconazole; amphotericin B was subsequently added, when a significant progression of cavitation was demonstrated on chest computed tomography. A. niger was not isolated in subsequent samples and the patient’s unfavorable outcome was attributed to septic shock caused by a pandrug-resistant Acinetobacter baumannii strain