Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201

Mutation in the xpsD gene of Xanthomonas axonopodis pv. citri affects cellulose degradation and virulence

The Gram-negative bacterium Xanthomonas axonopodis pv. citri, the causal agent of citrus canker, is a major threat to the citrus industry worldwide. Although this is a leaf spot pathogen, it bears genes highly related to degradation of plant cell walls, which are typically found in plant pathogens that cause symptoms of tissue maceration. Little is known on Xac capacity to cause disease and hydrolyze cellulose. We investigated the contribution of various open reading frames on degradation of a cellulose compound by means of a global mutational assay to selectively screen for a defect in carboxymethyl cellulase (CMCase) secretion in X. axonopodis pv. citri. Screening on CMC agar revealed one mutant clone defective in extracellular glycanase activity, out of nearly 3,000 clones. The insertion was located in the xpsD gene, a component of the type II secretion system (T2SS) showing an influence in the ability of Xac to colonize tissues and hydrolyze cellulose. In summary, these data show for the first time, that X. axonopodis pv. citri is capable of hydrolyzing cellulose in a T2SS-dependent process. Furthermore, it was demonstrated that the ability to degrade cellulose contributes to the infection process as a whole

The matricellular protein TSP1 promotes human and mouse endothelial cell senescence through CD47 and Nox1.

Senescent cells withdraw from the cell cycle and do not proliferate. The prevalence of senescent compared to normally functioning parenchymal cells increases with age, impairing tissue and organ homeostasis. A contentious principle governing this process has been the redox theory of aging. We linked matricellular protein thrombospondin 1 (TSP1) and its receptor CD47 to the activation of NADPH oxidase 1 (Nox1), but not of the other closely related Nox isoforms, and associated oxidative stress, and to senescence in human cells and aged tissue. In human endothelial cells, TSP1 promoted senescence and attenuated cell cycle progression and proliferation. At the molecular level, TSP1 increased Nox1-dependent generation of reactive oxygen species (ROS), leading to the increased abundance of the transcription factor p53. p53 mediated a DNA damage response that led to senescence through Rb and p21cip, both of which inhibit cell cycle progression. Nox1 inhibition blocked the ability of TSP1 to increase p53 nuclear localization and p21cip abundance and its ability to promote senescence. Mice lacking TSP1 showed decreases in ROS production, p21cip expression, p53 activity, and aging-induced senescence. Conversely, lung tissue from aging humans displayed increases in the abundance of vascular TSP1, Nox1, p53, and p21cip Finally, genetic ablation or pharmacological blockade of Nox1 in human endothelial cells attenuated TSP1-mediated ROS generation, restored cell cycle progression, and protected against senescence. Together, our results provide insights into the functional interplay between TSP1 and Nox1 in the regulation of endothelial senescence and suggest potential targets for controlling the aging process at the molecular level

Co-evolution of density and topology in a simple model of city formation

We study the influence that population density and the road network have on each others' growth and evolution. We use a simple model of formation and evolution of city roads which reproduces the most important empirical features of street networks in cities. Within this framework, we explicitely introduce the topology of the road network and analyze how it evolves and interact with the evolution of population density. We show that accessibility issues -pushing individuals to get closer to high centrality nodes- lead to high density regions and the appearance of densely populated centers. In particular, this model reproduces the empirical fact that the density profile decreases exponentially from a core district. In this simplified model, the size of the core district depends on the relative importance of transportation and rent costs.Comment: 13 pages, 13 figure

Endothelial Nox1 oxidase assembly in human pulmonary arterial hypertension; driver of Gremlin1-mediated proliferation.

Pulmonary arterial hypertension (PAH) is a rapidly degenerating and devastating disease of increased pulmonary vessel resistance leading to right heart failure. Palliative modalities remain limited despite recent endeavors to investigate the mechanisms underlying increased pulmonary vascular resistance (PVR), i.e. aberrant vascular remodeling and occlusion. However, little is known of the molecular mechanisms responsible for endothelial proliferation, a root cause of PAH-associated vascular remodeling. Lung tissue specimens from PAH and non-PAH patients and hypoxia-exposed human pulmonary artery endothelial cells (ECs) (HPAEC) were assessed for mRNA and protein expression. Reactive oxygen species (ROS) were measured using cytochrome c and Amplex Red assays. Findings demonstrate for the first time an up-regulation of NADPH oxidase 1 (Nox1) at the transcript and protein level in resistance vessels from PAH compared with non-PAH patients. This coincided with an increase in ROS production and expression of bone morphogenetic protein (BMP) antagonist Gremlin1 (Grem1). In HPAEC, hypoxia induced Nox1 subunit expression, assembly, and oxidase activity leading to elevation in sonic hedgehog (SHH) and Grem1 expression. Nox1 gene silencing abrogated this cascade. Moreover, loss of either Nox1, SHH or Grem1 attenuated hypoxia-induced EC proliferation. Together, these data support a Nox1-SHH-Grem1 signaling axis in pulmonary vascular endothelium that is likely to contribute to pathophysiological endothelial proliferation and the progression of PAH. These findings also support targeting of Nox1 as a viable therapeutic option to combat PAH

New insights into the classification and nomenclature of cortical GABAergic interneurons.

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus

Diffractive Dijet Production at sqrt(s)=630 and 1800 GeV at the Fermilab Tevatron

We report a measurement of the diffractive structure function $F_{jj}^D$ of the antiproton obtained from a study of dijet events produced in association with a leading antiproton in $\bar pp$ collisions at $\sqrt s=630$ GeV at the Fermilab Tevatron. The ratio of $F_{jj}^D$ at $\sqrt s=630$ GeV to $F_{jj}^D$ obtained from a similar measurement at $\sqrt s=1800$ GeV is compared with expectations from QCD factorization and with theoretical predictions. We also report a measurement of the $\xi$ ($x$-Pomeron) and $\beta$ ($x$ of parton in Pomeron) dependence of $F_{jj}^D$ at $\sqrt s=1800$ GeV. In the region $0.035<\xi<0.095$, $|t|<1$ GeV$^2$ and $\beta<0.5$, $F_{jj}^D(\beta,\xi)$ is found to be of the form $\beta^{-1.0\pm 0.1} \xi^{-0.9\pm 0.1}$, which obeys $\beta$-$\xi$ factorization.Comment: LaTeX, 9 pages, Submitted to Phys. Rev. Letter