41 research outputs found
Dynamic capacity provision for wireless sensors connectivity: A profit optimization approach
[EN] We model a wireless sensors' connectivity scenario mathematically and analyze it using capacity provision mechanisms, with the objective of maximizing the profits of a network operator. The scenario has several sensors' clusters with each one having one sink node, which uploads the sensing data gathered in the cluster through the wireless connectivity of a network operator. The scenario is analyzed both as a static game and as a dynamic game, each one with two stages, using game theory. The sinks' behavior is characterized with a utility function related to the mean service time and the price paid to the operator for the service. The objective of the operator is to maximize its profits by optimizing the network capacity. In the static game, the sinks' subscription decision is modeled using a population game. In the dynamic game, the sinks' behavior is modeled using an evolutionary game and the replicator dynamic, while the operator optimal capacity is obtained solving an optimal control problem. The scenario is shown feasible from an economic point of view. In addition, the dynamic capacity provision optimization is shown as a valid mechanism for maximizing the operator profits, as well as a useful tool to analyze evolving scenarios. Finally, the dynamic analysis opens the possibility to study more complex scenarios using the differential game extension.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Spanish Ministry of Economy and Competitiveness through project TIN2013-47272-C2-1-R; AEI/FEDER, UE through project TEC2017-85830-C2-1-P; and co-supported by the European Social Fund BES-2014-068998.Sanchis-Cano, Ă.; Guijarro, L.; Condoluci, M. (2018). Dynamic capacity provision for wireless sensors connectivity: A profit optimization approach. International Journal of Distributed Sensor Networks (Online). 14(4):1-14. https://doi.org/10.1177/1550147718772544S114144Weiser, M. (1991). The Computer for the 21st Century. Scientific American, 265(3), 94-104. doi:10.1038/scientificamerican0991-94Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660. doi:10.1016/j.future.2013.01.010Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2013). Sensing as a service model for smart cities supported by Internet of Things. Transactions on Emerging Telecommunications Technologies, 25(1), 81-93. doi:10.1002/ett.2704Wang, N., Hossain, E., & Bhargava, V. K. (2016). Joint Downlink Cell Association and Bandwidth Allocation for Wireless Backhauling in Two-Tier HetNets With Large-Scale Antenna Arrays. IEEE Transactions on Wireless Communications, 15(5), 3251-3268. doi:10.1109/twc.2016.2519401Chowdhury, M. Z., Jang, Y. M., & Haas, Z. J. (2013). Call admission control based on adaptive bandwidth allocation for wireless networks. Journal of Communications and Networks, 15(1), 15-24. doi:10.1109/jcn.2013.000005Nan, G., Mao, Z., Yu, M., Li, M., Wang, H., & Zhang, Y. (2014). Stackelberg Game for Bandwidth Allocation in Cloud-Based Wireless Live-Streaming Social Networks. IEEE Systems Journal, 8(1), 256-267. doi:10.1109/jsyst.2013.2253420Zhu, K., Niyato, D., Wang, P., & Han, Z. (2012). Dynamic Spectrum Leasing and Service Selection in Spectrum Secondary Market of Cognitive Radio Networks. IEEE Transactions on Wireless Communications, 11(3), 1136-1145. doi:10.1109/twc.2012.010312.110732Vamvakas, P., Tsiropoulou, E. E., & Papavassiliou, S. (2017). Dynamic Provider Selection & Power Resource Management in Competitive Wireless Communication Markets. Mobile Networks and Applications, 23(1), 86-99. doi:10.1007/s11036-017-0885-yNiyato, D., Hoang, D. T., Luong, N. C., Wang, P., Kim, D. I., & Han, Z. (2016). Smart data pricing models for the internet of things: a bundling strategy approach. IEEE Network, 30(2), 18-25. doi:10.1109/mnet.2016.7437020Guijarro, L., Pla, V., Vidal, J. R., & Naldi, M. (2016). Maximum-Profit Two-Sided Pricing in Service Platforms Based on Wireless Sensor Networks. IEEE Wireless Communications Letters, 5(1), 8-11. doi:10.1109/lwc.2015.2487259Romero, J., Guijarro, L., Pla, V., & Vidal, J. R. (2017). Price competition between a macrocell and a small-cell service provider with limited resources and optimal bandwidth user subscription: a game-theoretical model. Telecommunication Systems, 67(2), 195-209. doi:10.1007/s11235-017-0331-2Al Daoud, A., Alanyali, M., & Starobinski, D. (2010). Pricing Strategies for Spectrum Lease in Secondary Markets. IEEE/ACM Transactions on Networking, 18(2), 462-475. doi:10.1109/tnet.2009.2031176Do, C. T., Tran, N. H., Huh, E.-N., Hong, C. S., Niyato, D., & Han, Z. (2016). Dynamics of service selection and provider pricing game in heterogeneous cloud market. Journal of Network and Computer Applications, 69, 152-165. doi:10.1016/j.jnca.2016.04.012Tsiropoulou, E. E., Vamvakas, P., & Papavassiliou, S. (2017). Joint Customized Price and Power Control for Energy-Efficient Multi-Service Wireless Networks via S-Modular Theory. IEEE Transactions on Green Communications and Networking, 1(1), 17-28. doi:10.1109/tgcn.2017.2678207Sanchis-Cano, A., Romero, J., Sacoto-Cabrera, E., & Guijarro, L. (2017). Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator. Sensors, 17(12), 2727. doi:10.3390/s17122727Weber, T. A. (2011). Optimal Control Theory with Applications in Economics. doi:10.7551/mitpress/9780262015738.001.0001Mandjes, M. (2003). Pricing strategies under heterogeneous service requirements. Computer Networks, 42(2), 231-249. doi:10.1016/s1389-1286(03)00191-9Shariatmadari, H., Ratasuk, R., Iraji, S., Laya, A., Taleb, T., JĂ€ntti, R., & Ghosh, A. (2015). Machine-type communications: current status and future perspectives toward 5G systems. IEEE Communications Magazine, 53(9), 10-17. doi:10.1109/mcom.2015.7263367Ng, C.-H., & Soong, B.-H. (2008). Queueing Modelling Fundamentals. doi:10.1002/9780470994672Mendelson, H. (1985). Pricing computer services: queueing effects. Communications of the ACM, 28(3), 312-321. doi:10.1145/3166.3171Altman, E., Boulogne, T., El-Azouzi, R., JimĂ©nez, T., & Wynter, L. (2006). A survey on networking games in telecommunications. Computers & Operations Research, 33(2), 286-311. doi:10.1016/j.cor.2004.06.005Belleflamme, P., & Peitz, M. (2015). Industrial Organization. doi:10.1017/cbo9781107707139Reynolds, S. S. (1987). Capacity Investment, Preemption and Commitment in an Infinite Horizon Model. International Economic Review, 28(1), 69. doi:10.2307/2526860Barron, E. N. (2013). Game Theory. doi:10.1002/9781118547168Sandholm, W. (2009). Pairwise Comparison Dynamics and Evolutionary Foundations for Nash Equilibrium. Games, 1(1), 3-17. doi:10.3390/g1010003Schlag, K. H. (1998). Why Imitate, and If So, How? Journal of Economic Theory, 78(1), 130-156. doi:10.1006/jeth.1997.234
Sphinganine and sphingosine levels and ratio in urine and blood samples from a Catalonian population, Spain
Progress from ASDEX Upgrade experiments in preparing the physics basis of ITER operation and DEMO scenario development
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transientâs position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
Search for High-energy Neutrinos from Binary Neutron Star Merger GW170817 with ANTARES, IceCube, and the Pierre Auger Observatory
A gravitational-wave standard siren measurement of the Hubble constant
The detection of GW170817 (ref. 1) heralds the age of gravitational-wave multi-messenger astronomy, with the observations of gravitational-wave and electromagnetic emission from the same transient source. On 17 August 2017 the network of Advanced Laser Interferometer Gravitational-wave Observatory (LIGO)2 and Virgo3 detectors observed GW170817, a strong signal from the merger of a binary neutron-star system. Less than two seconds after the merger, a Îł-ray burst event, GRB 170817A, was detected consistent with the LIGOâVirgo sky localization region4â6). The sky region was subsequently observed by optical astronomy facilities7, resulting in the identification of an optical transient signal within about 10 arcseconds of the galaxy NGC 4993 (refs 8â13). GW170817 can be used as a standard siren14â18, combining the distance inferred purely from the gravitational-wave signal with the recession velocity arising from the electromagnetic data to determine the Hubble constant. This quantity, representing the local expansion rate of the Universe, sets the overall scale of the Universe and is of fundamental importance to cosmology. Our measurements do not require any form of cosmic âdistance ladderâ19; the gravitational-wave analysis directly estimates the luminosity distance out to cosmological scales. Here we report H0 = kilometres per second per megaparsec, which is consistent with existing measurements20,21, while being completely independent of them
Multi-messenger Observations of a Binary Neutron Star Merger
On 2017 August 17 a binary neutron star coalescence candidate (later
designated GW170817) with merger time 12:41:04 UTC was observed through
gravitational waves by the Advanced LIGO and Advanced Virgo detectors.
The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray
burst (GRB 170817A) with a time delay of ⌠1.7 {{s}} with respect to
the merger time. From the gravitational-wave signal, the source was
initially localized to a sky region of 31 deg2 at a
luminosity distance of {40}-8+8 Mpc and with
component masses consistent with neutron stars. The component masses
were later measured to be in the range 0.86 to 2.26 {M}ÈŻ
. An extensive observing campaign was launched across the
electromagnetic spectrum leading to the discovery of a bright optical
transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC
4993 (at ⌠40 {{Mpc}}) less than 11 hours after the merger by the
One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The
optical transient was independently detected by multiple teams within an
hour. Subsequent observations targeted the object and its environment.
Early ultraviolet observations revealed a blue transient that faded
within 48 hours. Optical and infrared observations showed a redward
evolution over âŒ10 days. Following early non-detections, X-ray and
radio emission were discovered at the transientâs position ⌠9
and ⌠16 days, respectively, after the merger. Both the X-ray and
radio emission likely arise from a physical process that is distinct
from the one that generates the UV/optical/near-infrared emission. No
ultra-high-energy gamma-rays and no neutrino candidates consistent with
the source were found in follow-up searches. These observations support
the hypothesis that GW170817 was produced by the merger of two neutron
stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and
a kilonova/macronova powered by the radioactive decay of r-process
nuclei synthesized in the ejecta.</p
Occurrence and Dietary Exposure Assessment to Enniatin B through Consumption of Cereal-Based Products in Spain and the Catalonia Region
Enniatin B (ENNB) is a mycotoxin produced by moulds from the Fusarium genera and its toxic effects are still not fully elucidated, hence a safe reference exposure value has not been established yet. ENNB is the most prevalent emerging mycotoxin and is widely found in cereal-based products, nevertheless, there are no comprehensive exposure assessment studies. For that reason, the aim of this study was to characterise the occurrence of ENNB and estimate the exposure of the Spanish and Catalan populations. A total of 347 cereal-based products were collected in 2019 and were analysed using liquid chromatography-tandem mass spectrometry. Consumption data were obtained from the national food consumption surveys (ENALIA) and a regional survey conducted in Catalonia. The global exposure was estimated using deterministic and probabilistic methods. The results showed a high occurrence of close to 100% in all foodstuffs, with a range from 6 to 269 ”g/kg, and a strong correlation with the levels of deoxynivalenol. Children aged oneânine years were the most exposed, showing mean estimates in the range 308â324 ng/kg bw/day and 95th percentiles 697â781 ng/kg bw/day. This study stresses the need for further toxicological data to establish reference doses and conclude formal risk assessment, accounting for the co-occurrence with deoxynivalenol
Cyclic peptideâpolymer nanotubes as efficient and highly potent drug delivery systems for organometallic anticancer complexes
Background and Purpose
Risk of cardiac conduction slowing (QRS/PR prolongations) is assessed prior to clinical trials using in vitro and in vivo studies. Understanding the quantitative translation of these studies to the clinical situation enables improved risk assessment in the nonclinical phase.
Experimental Approach
Four compounds that prolong QRS and/or PR (AZD1305, flecainide, quinidine and verapamil) were characterized using in vitro (sodium/calcium channels), in vivo (guinea pigs/dogs) and clinical data. Concentration-matched translational relationships were developed based on in vitro and in vivo modelling, and the in vitro to clinical translation of AZD1305 was quantified using an in vitro model.
Key Results
Meaningful (10%) human QRS/PR effects correlated with low levels of in vitro Nav1.5 block (3â7%) and Cav1.2 binding (13â21%) for all compounds. The in vitro model developed using AZD1305 successfully predicted QRS/PR effects for the remaining drugs. Meaningful QRS/PR changes in humans correlated with small effects in guinea pigs and dogs (QRS 2.3â4.6% and PR 2.3â10%), suggesting that worst-case human effects can be predicted by assuming four times greater effects at the same concentration from dog/guinea pig data.
Conclusion and Implications
Small changes in vitro and in vivo consistently translated to meaningful PR/QRS changes in humans across compounds. Assuming broad applicability of these approaches to assess cardiovascular safety risk for nonâarrhythmic drugs, this study provides a means of predicting human QRS/PR effects of new drugs from effects observed in nonclinical studies