Cellular processes associated with LRRK2 function and dysfunction.

Mutations in the leucine-rich repeat kinase 2 (LRRK2) encoding gene are the most common cause of monogenic Parkinson's Disease (PD). The identification of LRRK2 polymorphisms associated with increased risk for sporadic PD, as well as the observation that LRRK2-PD has an almost indistinguishable pathological phenotype from the sporadic form of disease, suggested LRRK2 as the culprit to provide understanding for both familial and sporadic PD cases. LRRK2 is a large protein with both GTPase and kinase functions. Mutations segregating with PD reside within the enzymatic core of LRRK2, suggesting the modification of its activity greatly impacts disease onset and progression. Although progress has been gained since its discovery in 2004, there is still much to be understood regarding LRRK2's physiological and neurotoxic properties. Unsurprisingly, given the presence of multiple enzymatic domains, LRRK2 has been associated with a diverse set of cellular functions and signalling pathways including mitochondrial function, vesicle trafficking together with endocytosis, retromer complex modulation and autophagy. This review will discuss the state of current knowledge for the role of LRRK2 in health and disease with discussion of potential substrates of phosphorylation and functional partners with particular emphasis on signalling mechanisms. As well, the use of immune cells in LRRK2 research and the role of oxidative stress as a regulator of LRRK2 activity and cellular function shall also be discussed. This article is protected by copyright. All rights reserved

Search for H → ττ in production processes in association with jets in CMS

A search for a light Higgs boson in the di-τ final state has been performed in CMS. Results, based on the 2011 data analysis and on an integrated luminosity corresponding to 4.6 fb−1 are presented and discussed along with the experimental issues related to the reconstruction of events in associated production processes

Relativistic Tunneling Through Two Successive Barriers

We study the relativistic quantum mechanical problem of a Dirac particle tunneling through two successive electrostatic barriers. Our aim is to study the emergence of the so-called \emph{Generalized Hartman Effect}, an effect observed in the context of nonrelativistic tunneling as well as in its electromagnetic counterparts, and which is often associated with the possibility of superluminal velocities in the tunneling process. We discuss the behavior of both the phase (or group) tunneling time and the dwell time, and show that in the limit of opaque barriers the relativistic theory also allows the emergence of the Generalized Hartman Effect. We compare our results with the nonrelativistic ones and discuss their interpretation.Comment: 7 pages, 3 figures. Revised version, with a new appendix added. Slightly changes in the styles and captions of Figures 1 and 2. To appear in Physical Review

International migration as occupational mobility

We investigate whether Germans immigrants to the US work in higher-status occupations than they would have had they remained in Germany. We account for potential bias from selective migration. The probability of migration is identified using life-cycle and cohort variation in economic conditions in the US. We also explore whether occupational choices vary for Germans who migrated as children or as adults. Our results allow us to decompose observed differences in occupational status of migrants and non migrants into the part explained by selection effects and the part that is causal, extending the literature on international migration

A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations

Within the framework of parameter dependent PDEs, we develop a constructive approach based on Deep Neural Networks for the efficient approximation of the parameter-to-solution map. The research is motivated by the limitations and drawbacks of state-of-the-art algorithms, such as the Reduced Basis method, when addressing problems that show a slow decay in the Kolmogorov n-width. Our work is based on the use of deep autoencoders, which we employ for encoding and decoding a high fidelity approximation of the solution manifold. In order to fully exploit the approximation capabilities of neural networks, we consider a nonlinear version of the Kolmogorov n-width over which we base the concept of a minimal latent dimension. We show that this minimal dimension is intimately related to the topological properties of the solution manifold, and we provide some theoretical results with particular emphasis on second order elliptic PDEs. Finally, we report numerical experiments where we compare the proposed approach with classical POD-Galerkin reduced order models. In particular, we consider parametrized advection-diffusion PDEs, and we test the methodology in the presence of strong transport fields, singular terms and stochastic coefficients

Casimir force on a piston

We consider a massless scalar field obeying Dirichlet boundary conditions on the walls of a two-dimensional L x b rectangular box, divided by a movable partition (piston) into two compartments of dimensions a x b and (L-a) x b. We compute the Casimir force on the piston in the limit L -> infinity. Regardless of the value of a/b, the piston is attracted to the nearest end of the box. Asymptotic expressions for the Casimir force on the piston are derived for a << b and a >> b.Comment: 10 pages, 1 figure. Final version, accepted for publication in Phys. Rev.

Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment

[EN] The logical separation of the data plane and the control plane of the network device conceptually defined by software-defined networking (SDN) creates many opportunities to create smart networking with better efficiency for network management and operation. SDN implementation over telecommunications (Telcos) and Internet service provider (ISP) networks is a challenging issue due to the lack of a high maturity level of SDN-based standards and several other critical factors that are considered during the real-time migration of existing legacy IPv4 networks. Different migration approaches have been studied; however, none of them seem to be close to realizing implementation. This paper implements the SDN-IP and Open Network Operating System (ONOS) SDN controller to migrate legacy IPv4 networks to multi-domain software-defined IPv6 (SoDIP6) networks and experimentally evaluate the viability of joint network migration in the ISP networks. We present results using extensive simulations for the suitable placement of the master ONOS controller during network migration by considering minimum control path latency using optimal path routing and the breadth first router replacement (BFR) technique. Our empirical analysis and evaluations show that the identification of the median router to attach the master controller and router migration planning using BFR give better results for carrier-grade legacy networks' migration to SoDIP6 networks.This research was partially funded by the Norwegian University of Science and Technology, Trondhiem, Norway (NTNU) under Sustainable Engineering Education Project (SEEP) financed by EnPE, University Grant Commission (grant-ID: FRG7475Engg01), Bhaktapur, Nepal, Nepal academy of Science and Technology (NAST), Kathmandu, Nepal, and U.S. National Science Foundation (NSF). The work of Danda B. Rawat was partly supported by the U.S. National Science Foundation (NSF) under grants CNS 1650831 and HRD 1828811. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the NSF. We are thankful to the ERASMUS+ KA107 project and the GRC lab team members at Universitat Politècnica De València for the research support and facilitation.Dawadi, BR.; Rawat, DB.; Joshi, SR.; Manzoni, P. (2020). Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment. Electronics. 9(9):1-22. https://doi.org/10.3390/electronics9091454S12299Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Software Defined IPv6 Network: A New Paradigm for Future Networking. Journal of the Institute of Engineering, 15(2), 1-13. doi:10.3126/jie.v15i2.27636Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Manzoni, P. (2020). Evolutionary gaming approach for decision making of Tier‐3 Internet service provider networks migration to SoDIP6 networks. International Journal of Communication Systems, 33(11). doi:10.1002/dac.4399Gu, D., Su, J., Xue, Y., Wang, D., Li, J., Luo, Z., & Yan, B. (2020). Modeling IPv6 adoption from biological evolution. Computer Communications, 158, 166-177. doi:10.1016/j.comcom.2020.02.081IPv6 Capability Measurement https://stats.labs.apnic.net/ipv6Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Keitsch, M. M. (2018). Joint Cost Estimation Approach for Service Provider Legacy Network Migration to Unified Software Defined IPv6 Network. 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC). doi:10.1109/cic.2018.00056Csikor, L., Szalay, M., Retvari, G., Pongracz, G., Pezaros, D. P., & Toka, L. (2020). Transition to SDN is HARMLESS: Hybrid Architecture for Migrating Legacy Ethernet Switches to SDN. IEEE/ACM Transactions on Networking, 28(1), 275-288. doi:10.1109/tnet.2019.2958762Sandhya, Sinha, Y., & Haribabu, K. (2017). A survey: Hybrid SDN. Journal of Network and Computer Applications, 100, 35-55. doi:10.1016/j.jnca.2017.10.003Mostafaei, H., Lospoto, G., Di Lallo, R., Rimondini, M., & Di Battista, G. (2020). A framework for multi‐provider virtual private networks in software‐defined federated networks. International Journal of Network Management, 30(6). doi:10.1002/nem.2116Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Evolutionary Dynamics of Service Provider Legacy Network Migration to Software Defined IPv6 Network. Advances in Intelligent Systems and Computing, 245-257. doi:10.1007/978-3-030-19861-9_24Salsano, S., Ventre, P. L., Lombardo, F., Siracusano, G., Gerola, M., Salvadori, E., … Prete, L. (2016). Hybrid IP/SDN Networking: Open Implementation and Experiment Management Tools. IEEE Transactions on Network and Service Management, 13(1), 138-153. doi:10.1109/tnsm.2015.2507622Vissicchio, S., Tilmans, O., Vanbever, L., & Rexford, J. (2015). Central Control Over Distributed Routing. Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication. doi:10.1145/2785956.2787497Rizvi, S. N., Raumer, D., Wohlfart, F., & Carle, G. (2015). Towards carrier grade SDNs. Computer Networks, 92, 218-226. doi:10.1016/j.comnet.2015.09.029Risdianto, A. C., Tsai, P.-W., Ling, T. C., Yang, C.-S., & Kim, J. (2017). Enhanced Onos Sdn Controllers Deployment For Federated Multi-Domain Sdn-Cloud With Sd-Routing-Exchange. Malaysian Journal of Computer Science, 30(2), 134-153. doi:10.22452/mjcs.vol30no2.5Ventre, P. L., Salsano, S., Gerola, M., Salvadori, E., Usman, M., Buscaglione, S., … Snow, W. (2017). SDN-Based IP and Layer 2 Services with an Open Networking Operating System in the GÉANT Service Provider Network. IEEE Communications Magazine, 55(4), 71-79. doi:10.1109/mcom.2017.1600194SDN-IP Arhitecture https://wiki.onosproject.org/display/ONOS/SDN-IP+ArchitectureLee, H.-L., Liu, T.-L., & Chen, M. (2019). Deploying SDN-IP over Transnational Network Testbed. 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). doi:10.1109/icce-tw46550.2019.8991776Das, T., Sridharan, V., & Gurusamy, M. (2020). A Survey on Controller Placement in SDN. IEEE Communications Surveys & Tutorials, 22(1), 472-503. doi:10.1109/comst.2019.2935453Chen, W., Chen, C., Jiang, X., & Liu, L. (2018). Multi-Controller Placement Towards SDN Based on Louvain Heuristic Algorithm. IEEE Access, 6, 49486-49497. doi:10.1109/access.2018.2867931Qi, Y., Wang, D., Yao, W., Li, H., & Cao, Y. (2019). Towards Multi-Controller Placement for SDN Based on Density Peaks Clustering. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). doi:10.1109/icc.2019.8761814Lu, J., Zhang, Z., Hu, T., Yi, P., & Lan, J. (2019). A Survey of Controller Placement Problem in Software-Defined Networking. IEEE Access, 7, 24290-24307. doi:10.1109/access.2019.2893283Singh, A. K., Maurya, S., Kumar, N., & Srivastava, S. (2019). Heuristic approaches for the reliable SDN controller placement problem. Transactions on Emerging Telecommunications Technologies, 31(2). doi:10.1002/ett.3761Das, T., & Gurusamy, M. (2018). Resilient Controller Placement in Hybrid SDN&#x002F;Legacy Networks. 2018 IEEE Global Communications Conference (GLOBECOM). doi:10.1109/glocom.2018.8647566Heller, B., Sherwood, R., & McKeown, N. (2012). The controller placement problem. ACM SIGCOMM Computer Communication Review, 42(4), 473-478. doi:10.1145/2377677.2377767SDN Control Plane Performance: Raising the Bar on SDN Performance, Scalability, and High Availability https://wiki.onosproject.org/download/attachments/13994369/Whitepaper-%20ONOS%20Kingfisher%20release%20performance.pdf?version=

Towards Collective Sentiment Analysis in IoT-Enabled Scenarios

An interesting and innovative activity in Collective Intelligence systems is Sentiment Analysis (SA) which, starting from users' feedback, aims to identify their opinion about a specific subject, for example in order to develop/improve/customize products and services. The feedback gathering, however, is complex, time-consuming, and often invasive, possibly resulting in decreased truthfulness and reliability for its outcome. Moreover, the subsequent feedback processing may suffer from scalability, cost, and privacy issues when the sample size is large or the data to be processed is sensitive. Internet of Things (IoT) and Edge Intelligence (EI) can greatly help in both aspects by providing, respectively, a pervasive and transparent way to collect a huge amount of heterogeneous data from users (e.g., audio, images, video, etc.) and an efficient, low-cost, and privacy-preserving solution to locally analyze them without resorting to Cloud computing-based platforms. Therefore, in this paper we outline an innovative collective SA system which leverages on IoT and EI (specifically, TinyML techniques and the EdgeImpulse platform) to gather and immediately process audio in the proximity of entities-of-interest in order to determine whether audience' opinions are positive, negative, or neutral. The architecture of the proposed system, exemplified in a museum use case, is presented, and a preliminary, yet very promising, implementation is shown, reveling interesting insights towards its full development