Practical applications using multi-UAV systems and aerial robotic swarms

[EN] Nowadays, there are a large number of unmanned aircraft on the market that can be commanded with high-level orders to perform complex tasks almost automatically, such as mapping crop fields. We can ask ourselves if it would be possible to coordinate a group of these robots to perform those same tasks more quickly, flexibly and robustly. In this work, we summarize the tasks that have been studied to be solved with systems composed by groups of unmanned aircraft and the algorithms used, as well as the methods and strategies on which they are based. Although the future of these systems is promising, there are certain legislative and technical obstacles that stop their implementation in a generalized way.[ES] A día de hoy, existen en el mercado una gran cantidad de aeronaves sin piloto que pueden ser comandadas con ordenes de alto nivel para realizar tareas complejas de forma casi automatica, como por ejemplo el mapeo de explotaciones agrícolas. De forma natural, nos podemos preguntar si sería posible coordinar a un grupo de estos robots para realizar esas mismas tareas de forma más rápida, flexible y robusta. En este trabajo se repasan las tareas que se han planteado resolver con sistemas compuestos por grupos de aeronaves no tripuladas y los algoritmos empleados, así como los metodos y estrategias en los que están basados. Aunque el futuro de estos sistemas es prometedor, existen ciertos obstaculos legislativos y técnicos que frenan su implantación de forma generalizada.Las investigaciones que han dado como resultado este trabajo han sido financiadas por RoboCity2030-DIH-CM, 426 Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, financiadas por los Programas de Actividades I+D en la Comunidad Madrid, y por el proyecto TASAR (Team of Advanced Search And Rescue Robots), PID2019-105808RB-I00, financiado por el Ministerio de Ciencia e Innovacion (Gobierno de España).García-Aunon, P.; Roldán, J.; De León, J.; Del Cerro, J.; Barrientos, A. (2021). Aplicaciones practicas de los sistemas multi-UAV y enjambres aéreos. Revista Iberoamericana de Automática e Informática industrial. 18(3):230-241. https://doi.org/10.4995/riai.2020.13560OJS230241183Acevedo, J. J., Arrue, B. C., Maza, I., Ollero, A., 2013. Cooperative large area surveillance with a team of aerial mobile robots for long endurance missions. Journal of Intelligent & Robotic Systems 70 (1-4), 329-345. https://doi.org/10.1007/s10846-012-9716-3Albani, D., IJsselmuiden, J., Haken, R., Trianni, V., 2017. Monitoring and mapping with robot swarms for agricultural applications. In: 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE, pp. 1-6. https://doi.org/10.1109/AVSS.2017.8078478Alvear, O., Zema, N. R., Natalizio, E., Calafate, C. T., 2017. Using uav-based systems to monitor air pollution in areas with poor accessibility. Journal of Advanced Transportation 2017. https://doi.org/10.1155/2017/8204353Augugliaro, F., Lupashin, S., Hamer, M., Male, C., Hehn, M., Mueller, M. W., Willmann, J. S., Gramazio, F., Kohler, M., D'Andrea, R., 2014. The flight assembled architecture installation: Cooperative construction with flying machines. IEEE Control Systems Magazine 34 (4), 46-64. https://doi.org/10.1109/MCS.2014.2320359Barrientos, A., Colorado, J., Cerro, J. d., Martinez, A., Rossi, C., Sanz, D., Valente, J., 2011. Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots. Journal of Field Robotics 28 (5), 667-689. https://doi.org/10.1002/rob.20403Beck, Z., Teacy, W. L., Rogers, A., Jennings, N. R., 2018. Collaborative online planning for automated victim search in disaster response. Robotics and Autonomous Systems 100, 251-266. https://doi.org/10.1016/j.robot.2017.09.014Bennet, D. J., MacInnes, C., Suzuki, M., Uchiyama, K., 2011. Autonomous three-dimensional formation flight for a swarm of unmanned aerial vehicles. Journal of guidance, control, and dynamics 34 (6), 1899-1908. https://doi.org/10.2514/1.53931Bernard, M., Kondak, K., Maza, I., Ollero, A., 2011. Autonomous transportation and deployment with aerial robots for search and rescue missions. Journal of Field Robotics 28 (6), 914-931. https://doi.org/10.1002/rob.20401Carrasco, Á. M., Novoa, S. C., Al-Kaff, A., Fernández, F. G., Gómez, D. M., de la Escalera Hueso, A., 2020. Vehículo aéreo no tripulado para vigilancia y monitorización de incendios. Revista Iberoamericana de Automática e Informática industrial.Chen, S., Li, C., Zhuo, S., 2017. A distributed coverage algorithm for multiuav with average voronoi partition. In: 2017 17th International Conference on Control, Automation and Systems (ICCAS). IEEE, pp. 1083-1086. https://doi.org/10.23919/ICCAS.2017.8204377Cieslewski, T., Choudhary, S., Scaramuzza, D., 2018. Data-efficient decentralized visual slam. In: 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 2466-2473. https://doi.org/10.1109/ICRA.2018.8461155Cimino, M. G., Lazzeri, A., Vaglini, G., 2015. Combining stigmergic and flocking behaviors to coordinate swarms of drones performing target search. In: 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA). IEEE, pp. 1-6. https://doi.org/10.1109/IISA.2015.7387990Cledat, E., Cucci, D., 2017. Mapping gnss restricted environments with a drone tandem and indirect position control. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 4, 1. https://doi.org/10.5194/isprs-annals-IV-2-W3-1-2017Cole, D. T., Thompson, P., Göktogan, A. H., Sukkarieh, S., 2010. System development and demonstration of a cooperative uav team for mapping and tracking. The International Journal of Robotics Research 29 (11), 1371-1399. https://doi.org/10.1177/0278364910364685Darrah, M., Trujillo, M. M., Speransky, K., Wathen, M., 2017. Optimized 3d mapping of a large area with structures using multiple multirotors. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp. 716-722. https://doi.org/10.1109/ICUAS.2017.7991414Erignac, C., 2007. An exhaustive swarming search strategy based on distributed pheromone maps. In: AIAA Infotech@ Aerospace 2007 Conference and Exhibit. p. 2822. https://doi.org/10.2514/6.2007-2822Fu, Z., Chen, Y., Ding, Y., He, D., 2019. Pollution source localization based on multi-uav cooperative communication. IEEE Access 7, 29304-29312. https://doi.org/10.1109/ACCESS.2019.2900475Fujisawa, R., Imamura, H., Hashimoto, T., Matsuno, F., 2008. Communication using pheromone field for multiple robots. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, pp. 1391-1396. https://doi.org/10.1109/IROS.2008.4650971Garcia-Aunon, P., Barrientos, A., 2018a. Comparison of heuristic algorithms in discrete search and surveillance tasks using aerial swarms. Applied Sciences 8 (5), 711. https://doi.org/10.3390/app8050711Garcia-Aunon, P., Barrientos, A., 2018b. Control optimization of an aerial robotic swarm in a search task and its adaptation to different scenarios. Journal of computational science 29, 107-118. https://doi.org/10.1016/j.jocs.2018.10.004Garcia-Aunon, P., del Cerro, J., Barrientos, A., 2019a. Behavior-based control for an aerial robotic swarm in surveillance missions. Sensors 19 (20), 4584. https://doi.org/10.3390/s19204584Garcia-Aunon, P., Roldan, J. J., Barrientos, A., 2019b. Monitoring traffic in future cities with aerial swarms: Developing and optimizing a behavior-based surveillance algorithm. Cognitive Systems Research 54, 273-286. https://doi.org/10.1016/j.cogsys.2018.10.031Garnier, S., Tache, F., Combe, M., Grimal, A., Theraulaz, G., 2007. Alice in pheromone land: An experimental setup for the study of ant-like robots. In: 2007 IEEE Swarm Intelligence Symposium. IEEE, pp. 37-44. https://doi.org/10.1109/SIS.2007.368024George, J., Sujit, P., Sousa, J. B., 2011. Search strategies for multiple uav search and destroy missions. Journal of Intelligent & Robotic Systems 61 (1-4), 355-367. https://doi.org/10.1007/s10846-010-9486-8Hadaegh, F. Y., Chung, S.-J., Manohara, H. M., 2014. On development of 100- gram-class spacecraft for swarm applications. IEEE Systems Journal 10 (2), 673-684. https://doi.org/10.1109/JSYST.2014.2327972Han, J., Xu, Y., Di, L., Chen, Y., 2013. Low-cost multi-uav technologies for contour mapping of nuclear radiation field. Journal of Intelligent & Robotic Systems 70 (1-4), 401-410. https://doi.org/10.1007/s10846-012-9722-5Hauert, S., Winkler, L., Zufferey, J.-C., Floreano, D., 2008. Ant-based swarming with positionless micro air vehicles for communication relay. Swarm Intelligence 2 (2-4), 167-188. https://doi.org/10.1007/s11721-008-0013-5Hinzmann, T., Stastny, T., Conte, G., Doherty, P., Rudol, P., Wzorek, M., Galceran, E., Siegwart, R., Gilitschenski, I., 2016. Collaborative 3d reconstruction using heterogeneous uavs: System and experiments. In: International Symposium on Experimental Robotics. Springer, pp. 43-56. https://doi.org/10.1007/978-3-319-50115-4_5Ju, C., Son, H., 2018. Multiple uav systems for agricultural applications: control, implementation, and evaluation. Electronics 7 (9), 162. https://doi.org/10.3390/electronics7090162Kim, J. H., Kwon, J.-W., Seo, J., 2014. Multi-uav-based stereo vision system without gps for ground obstacle mapping to assist path planning of ugv. Electronics Letters 50 (20), 1431-1432. https://doi.org/10.1049/el.2014.2227Lanillos, P., Gan, S. K., Besada-Portas, E., Pajares, G., Sukkarieh, S., 2014. Multi-uav target search using decentralized gradient-based negotiation with expected observation. Information Sciences 282, 92-110. https://doi.org/10.1016/j.ins.2014.05.054Li, W., 2015. Persistent surveillance for a swarm of micro aerial vehicles by flocking algorithm. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 229 (1), 185-194. https://doi.org/10.1177/0954410014529100Lyu, Y., Pan, Q., Zhang, Y., Zhao, C., Zhu, H., Tang, T., Liu, L., 2015. Simultaneously multi-uav mapping and control with visual servoing. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp. 125-131. https://doi.org/10.1109/ICUAS.2015.7152283Mahdoui, N., Frémont, V., Natalizio, E., 2017. Cooperative exploration strategy for micro-aerial vehicles fleet. In: 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI). IEEE, pp. 180-185. https://doi.org/10.1109/MFI.2017.8170426Maza, I., Ollero, A., 2007. Multiple uav cooperative searching operation using polygon area decomposition and efficient coverage algorithms. In: Distributed Autonomous Robotic Systems 6. Springer, pp. 221-230. https://doi.org/10.1007/978-4-431-35873-2_22Mirjan, A., Gramazio, F., Kohler, M., Augugliaro, F., D'Andrea, R., 2013. Architectural fabrication of tensile structures with flying machines. Green Design, Materials and Manufacturing Processes, 513-518. https://doi.org/10.1201/b15002-99Niedzielski, T., Jurecka, M., Mizinski, B., Remisz, J., Slopek, J., Spallek, W., Witek-Kasprzak, M., Kasprzak, Ł., Swierczynska-Chlasciak, M., 2018. A real-time field experiment on search and rescue operations assisted by unmanned aerial vehicles. Journal of Field Robotics 35 (6), 906-920. https://doi.org/10.1002/rob.21784Nigam, N., Bieniawski, S., Kroo, I., Vian, J., 2011. Control of multiple uavs for persistent surveillance: algorithm and flight test results. IEEE Transactions on Control Systems Technology 20 (5), 1236-1251. https://doi.org/10.1109/TCST.2011.2167331Odonkor, P., Ball, Z., Chowdhury, S., 2019. Distributed operation of collaborating unmanned aerial vehicles for time-sensitive oil spill mapping. Swarm and Evolutionary Computation 46, 52-68. https://doi.org/10.1016/j.swevo.2019.01.005Oh, S.-H., Suk, J., 2010. Evolutionary design of the controller for the search of area with obstacles using multiple uavs. In: ICCAS 2010. IEEE, pp. 2541- 2546. https://doi.org/10.1109/ICCAS.2010.5670230Perez-Carabaza, S., Besada-Portas, E., Lopez-Orozco, J. A., Jesus, M., 2018. Ant colony optimization for multi-uav minimum time search in uncertain domains. Applied Soft Computing 62, 789-806. https://doi.org/10.1016/j.asoc.2017.09.009Qu, Y., Zhang, Y., Zhang, Y., 2015. A uav solution of regional surveillance based on pheromones and artificial potential field theory. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp. 380-385. https://doi.org/10.1109/ICUAS.2015.7152313Rastgoftar, H., Atkins, E. M., 2018. Cooperative aerial lift and manipulation (calm). Aerospace Science and Technology 82, 105-118. https://doi.org/10.1016/j.ast.2018.09.005Reina, D., Tawfik, H., Toral, S., 2018. Multi-subpopulation evolutionary algorithms for coverage deployment of uav-networks. Ad Hoc Networks 68, 16-32. https://doi.org/10.1016/j.adhoc.2017.09.005Reuder, J., Jonassen, M. O., Olafsson, H., 2012. The small unmanned meteorological observer sumo: Recent developments and applications of a micro-uas for atmospheric boundary layer research. Acta Geophysica 60 (5), 1454- 1473. https://doi.org/10.2478/s11600-012-0042-8Reynolds, C. W., 1987. Flocks, herds and schools: A distributed behavioral model. Vol. 21. ACM. https://doi.org/10.1145/37402.37406Roldan, J. J., Garcia-Aunon, P., Peña-Tapia, E., Barrientos, A., 2019. Swarm-city project: Can an aerial swarm monitor traffic in a smart city? In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, pp. 862-867. https://doi.org/10.1109/PERCOMW.2019.8730677Santamaria, E., Segor, F., Tchouchenkov, I., 2013. Rapid aerial mapping with multiple heterogeneous unmanned vehicles. In: ISCRAM. Citeseer.Saska, M., Chudoba, J., Preucil, L., Thomas, J., Loianno, G., Tresnak, A., Vonasek, V., Kumar, V., 2014. Autonomous deployment of swarms of microaerial vehicles in cooperative surveillance. In: 2014 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp. 584-595. https://doi.org/10.1109/ICUAS.2014.6842301Savkin, A. V., Huang, H., 2019. Asymptotically optimal deployment of drones for surveillance and monitoring. Sensors 19 (9), 2068. https://doi.org/10.3390/s19092068Schilling, F., Lecoeur, J., Schiano, F., Floreano, D., 2018. Learning visionbased cohesive flight in drone swarms. arXiv preprint arXiv:1809.00543.Schmuck, P., Chli, M., 2017. Multi-uav collaborative monocular slam. In: 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 3863-3870. https://doi.org/10.1109/ICRA.2017.7989445Silic, M. B., Song, Z., Mohseni, K., 2018. Anisotropic flocking control of distributed multi-agent systems using fluid abstraction. In: 2018 AIAA Information Systems-AIAA Infotech@ Aerospace. p. 2262. https://doi.org/10.2514/6.2018-2262Sreenath, K., Kumar, V., 2013. Dynamics, control and planning for cooperative manipulation of payloads suspended by cables from multiple quadrotor robots. rn 1 (r2), r3. https://doi.org/10.15607/RSS.2013.IX.011St-Onge, D., Kaufmann, M., Panerati, J., Ramtoula, B., Cao, Y., Coffey, E. B., Beltrame, G., 2019. Planetary exploration with robot teams. IEEE Robotics & Automation Magazine.Stavros, E. N., Agha, A., Sirota, A., Quadrelli, M., Ebadi, K., Yun, K., 2019. Smoke sky-exploring new frontiers of unmanned aerial systems for wildland fire science and applications. arXiv preprint arXiv:1911.08288.Techy, L., Schmale III, D. G., Woolsey, C. A., 2010. Coordinated aerobiological sampling of a plant pathogen in the lower atmosphere using two autonomous unmanned aerial vehicles. Journal of Field Robotics 27 (3), 335-343. https://doi.org/10.1002/rob.20335Tuna, G., Nefzi, B., Conte, G., 2014. Unmanned aerial vehicle-aided communications system for disaster recovery. Journal of Network and Computer Applications 41, 27-36. https://doi.org/10.1016/j.jnca.2013.10.002Twidwell, D., Allen, C. R., Detweiler, C., Higgins, J., Laney, C., Elbaum, S., 2016. Smokey comes of age: unmanned aerial systems for fire management. Frontiers in Ecology and the Environment 14 (6), 333-339. https://doi.org/10.1002/fee.1299Vasarhelyi, G., Viragh, C., Somorjai, G., Tarcai, N., Szorenyi, T., Nepusz, T., Vicsek, T., 2014. Outdoor flocking and formation flight with autonomous aerial robots. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, pp. 3866-3873. https://doi.org/10.1109/IROS.2014.6943105Verdu, T., Hattenberger, G., Lacroix, S., 2019. Flight patterns for clouds exploration with a fleet of uavs. https://doi.org/10.1109/ICUAS.2019.8797953Waharte, S., Trigoni, N., 2010. Supporting search and rescue operations with uavs. In: 2010 International Conference on Emerging Security Technologies. IEEE, pp. 142-147. https://doi.org/10.1109/EST.2010.31Wang, Z., Singh, S., Pavone, M., Schwager, M., 2018. Cooperative object transport in 3d with multiple quadrotors using no peer communication. In: 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 1064-1071. https://doi.org/10.1109/ICRA.2018.8460742Zhao, N., Lu, W., Sheng, M., Chen, Y., Tang, J., Yu, F. R., Wong, K.-K., 2019. Uav-assisted emergency networks in disasters. IEEE Wireless Communications 26 (1), 45-51. https://doi.org/10.1109/MWC.2018.1800160Zheng, X., Wang, F., Li, Z., 2018. A multi-uav cooperative route planning methodology for 3d fine-resolution building model reconstruction. ISPRS journal of photogrammetry and remote sensing 146, 483-494. https://doi.org/10.1016/j.isprsjprs.2018.11.00

Nuevos fármacos antiepilépticos en Pediatría

Se estima que unos 70 millones de personas padecen epilepsia a nivel mundial de los cuales más de la mitad son niños, en los que la prevalencia estimada se sitúa en torno al 0,5-0,8%. Aunque existen diversas terapias, el tratamiento de la epilepsia se basa mayoritariamente en fármacos, que en función de su año de comercialización se clasifican como de primera, segunda o tercera generación. En el presente artículo se revisan las principales características de los fármacos antiepilépticos de última generación (lacosamida, acetato de eslicarbazepina, brivaracetam, perampanel, retigabina, everolimus y cannabidiol) que, con excepción de la retigabina (ya no está comercializada), se consideran seguros y efectivos en población pediátrica. El everolimus y el cannabidiol tienen indicaciones muy concretas (esclerosis tuberosa, síndrome de Dravet y síndrome de Lennox Gastaut) mientras que el resto están indicados en el manejo de crisis de origen focal en niños a partir de 4 años. Estas nuevas moléculas han sido desarrolladas para aportar un perfil farmacocinético y de tolerancia superior a los fármacos previamente disponibles y es previsible que a medida que aumente su uso, se vaya perfilando y ampliando su verdadero potencial. Además, por primera vez en epileptología pediátrica, se ha utilizado la extrapolación de datos de efectividad en adultos (junto con estudios de seguridad y farmacocinética específicos en población pediátrica), para acelerar la aprobación de uso en población infantil.It is estimated that about 70 million people all over the world suffer from epilepsy, half of which are children, in whom the prevalence is around 0.5 to 0.8%. Although there are several therapies, the treatment of epilepsy is based mainly on drugs, which, depending on the year of coming onto the market are classified as first, second, or third generation. In this article, a description is presented on the main characteristics of the latest generation of antiepileptic drugs (lacosamide, eslicarbazepine acetate, brivaracetam, perampanel, retigabine, everolimus and cannabidiol). These, with the exception of retigabine (is not yet on the market), are considered safe and effective in the paediatric population. Everolimus and cannabidiol have very specific indications (tuberous sclerosis, Dravet syndrome, and Lennox Gastaut syndrome), while the rest are indicated in the management of seizures of focal origin in children from 4 years-old. These new molecules have been developed in order to provide a pharmaceutical profile and tolerance superior to the previously available drugs, and it is forecast that as their use increases, their true potential and profile will widen. Furthermore, for the first time in Paediatric Epileptology,the extrapolation ofthe efficacy data in adults have been used (together with specific safety and pharmacokinetic studies in the paediatric population), in order to speed up their approval for use in the child population

Mindfulness-based program for anxiety and depression treatment in healthcare professionals: A pilot randomized controlled trial

In primary health care, the work environment can cause high levels of anxiety and depression, triggering relevant expert and individual change. Mindfulness-Based Stress Reduction (MBSR) programs reduce signs of anxiety and depression. The purpose of this sub-analysis of the total project, was to equate the effectiveness of the standard MBSR curriculum with the abbreviated version in minimizing anxiety and depression. This randomized controlled clinical trial enrolled 112 mentors and resident specialists from Family and Community Medicine and Nurses (FCMN), distributed across six teaching units (TU) of the Spanish National Health System (SNHS). Experimental group participants received a MBRS training (abbreviated/standard). Depression and anxiety levels were measured with the Goldberg Anxiety and Depression Scale (GADS) at three different time periods during the analysis: before (pre-test) and after (post-test) participation, as well as 3 months after the completion of intervention. Taking into account the pre-test scores as the covariate, an adjusted analysis of covariance (ANCOVA) showed significant depletion in anxiety and depression in general (F (2.91) = 4.488; p = 0.014; ¿2 = 0.090) and depression in particular (F (2, 91) = 6.653; p = 0.002; ¿2 = 0.128 at the post-test visit, maintaining their effects for 3 months (F (2.79) = 3.031; p = 0.050; ¿2 = 0.071—F (2.79) = 2.874; p = 0.049; ¿2 = 0.068, respectively), which is associated with the use of a standard training program. The abbreviated training program did not have a significant effect on the level of anxiety and depression. The standard MBSR training program had a positive effect on anxiety and depression and promotes long-lasting effects in tutors and resident practitioners. New research is needed to demonstrate the effectiveness of abbreviated versions of training programs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

D* Production in Deep Inelastic Scattering at HERA

This paper presents measurements of D^{*\pm} production in deep inelastic scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The data have been taken with the ZEUS detector at HERA. The decay channel $D^{*+}\to (D^0 \to K^- \pi^+) \pi^+$ (+ c.c.) has been used in the study. The $e^+p$ cross section for inclusive D^{*\pm} production with $5<Q^2<100 GeV^2$ and $y<0.7$ is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region {$1.3<p_T(D^{*\pm})<9.0$ GeV and $| \eta(D^{*\pm}) |<1.5$}. Differential cross sections as functions of p_T(D^{*\pm}), $\eta(D^{*\pm}), W$ and $Q^2$ are compared with next-to-leading order QCD calculations based on the photon-gluon fusion production mechanism. After an extrapolation of the cross section to the full kinematic region in p_T(D^{*\pm}) and $\eta$(D^{*\pm}), the charm contribution $F_2^{c\bar{c}}(x,Q^2)$ to the proton structure function is determined for Bjorken $x$ between 2 $\cdot$ 10$^{-4}$ and 5 $\cdot$ 10$^{-3}$.Comment: 17 pages including 4 figure

Observation of Scaling Violations in Scaled Momentum Distributions at HERA

Charged particle production has been measured in deep inelastic scattering (DIS) events over a large range of $x$ and $Q^2$ using the ZEUS detector. The evolution of the scaled momentum, $x_p$, with $Q^2,$ in the range 10 to 1280 $GeV^2$, has been investigated in the current fragmentation region of the Breit frame. The results show clear evidence, in a single experiment, for scaling violations in scaled momenta as a function of $Q^2$.Comment: 21 pages including 4 figures, to be published in Physics Letters B. Two references adde

Observation of hard scattering in photoproduction events with a large rapidity gap at HERA

Events with a large rapidity gap and total transverse energy greater than 5 GeV have been observed in quasi-real photoproduction at HERA with the ZEUS detector. The distribution of these events as a function of the $\gamma p$ centre of mass energy is consistent with diffractive scattering. For total transverse energies above 12 GeV, the hadronic final states show predominantly a two-jet structure with each jet having a transverse energy greater than 4 GeV. For the two-jet events, little energy flow is found outside the jets. This observation is consistent with the hard scattering of a quasi-real photon with a colourless object in the proton.Comment: 19 pages, latex, 4 figures appended as uuencoded fil

Spread of a SARS-CoV-2 variant through Europe in the summer of 2020.

Following its emergence in late 2019, the spread of SARS-CoV-21,2 has been tracked by phylogenetic analysis of viral genome sequences in unprecedented detail3–5. Although the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced. However, travel within Europe resumed in the summer of 2020. Here we report on a SARS-CoV-2 variant, 20E (EU1), that was identified in Spain in early summer 2020 and subsequently spread across Europe. We find no evidence that this variant has increased transmissibility, but instead demonstrate how rising incidence in Spain, resumption of travel, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions, we estimate that 20E (EU1) was introduced hundreds of times to European countries by summertime travellers, which is likely to have undermined local efforts to minimize infection with SARS-CoV-2. Our results illustrate how a variant can rapidly become dominant even in the absence of a substantial transmission advantage in favourable epidemiological settings. Genomic surveillance is critical for understanding how travel can affect transmission of SARS-CoV-2, and thus for informing future containment strategies as travel resumes. © 2021, The Author(s), under exclusive licence to Springer Nature Limited

Phylogenomic analysis of a 55.1 kb 19-gene dataset resolves a monophyletic Fusarium that includes the Fusarium solani Species Complex

Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user¿s needs and established successful practice. In 2013, the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani species complex (FSSC). Subsequently, this concept was challenged in 2015 by one research group who proposed dividing the genus Fusarium into seven genera, including the FSSC described as members of the genus Neocosmospora, with subsequent justification in 2018 based on claims that the 2013 concept of Fusarium is polyphyletic. Here, we test this claim and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a genus Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students, and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species described as genus Neocosmospora were recombined in genus Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural, and practical taxonomic option availabl

Observation of Events with an Energetic Forward Neutron in Deep Inelastic Scattering at HERA

In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample independent of Bjorken x and Q2 in the range 3 · 10-4 \u3c xBJ \u3c 6 · 10-3 and 10 \u3c Q2 \u3c 100 GeV2